Syntactic Boostrapping MA
Data V2
Anjie Cao and Molly Lewis
2020-07-17
DATA_PATH <- here("data/processed/syntactic_bootstrapping_tidy_data.csv") # make all variables (i.e. things that might change) as capital letters at the top of the scripts
ma_data <- read_csv(DATA_PATH) %>%
filter(language == "English",
population_type == "typically_developing",
stimuli_modality == "video"|stimuli_modality == "animation",
!is.na(mean_age))
ma_data## # A tibble: 105 x 55
## x1 coder unique_id link grammatical_cla… paper_eligibili… short_cite
## <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 1 alan… arunacha… http… verb include Arunachal…
## 2 2 alan… arunacha… http… verb include Arunachal…
## 3 3 alan… arunacha… http… verb include Arunachal…
## 4 4 alan… arunacha… http… verb include Arunachal…
## 5 5 alan… arunacha… http… verb include Arunachal…
## 6 6 anjie arunacha… http… verb include Arunachal…
## 7 7 anjie arunacha… http… verb include Arunachal…
## 8 8 alan… bunger20… http… verb include Bunger, A…
## 9 9 alan… bunger20… http… verb include Bunger, A…
## 10 10 alan… bunger20… http… verb include Bunger, A…
## # … with 95 more rows, and 48 more variables: data_source <chr>,
## # expt_num <chr>, expt_condition <chr>, dependent_measure <chr>,
## # test_type <chr>, same_infant <chr>, language <chr>, mean_age <dbl>,
## # productive_vocab_mean <dbl>, productive_vocab_median <dbl>,
## # population_type <chr>, sentence_structure <chr>, agent_argument_type <chr>,
## # patient_argument_type <chr>, verb_type <chr>, stimuli_type <chr>,
## # stimuli_modality <chr>, stimuli_actor <chr>, presentation_type <chr>,
## # character_identification <chr>, practice_phase <chr>,
## # test_mass_or_distributed <chr>, n_train_test_pair <dbl>,
## # n_test_trial_per_pair <dbl>, n_repetitions_sentence <dbl>,
## # n_repetitions_video <dbl>, example_target_sentence <chr>,
## # test_question <chr>, inclusion_certainty <dbl>, note <chr>, n_1 <dbl>,
## # x_1 <dbl>, x_2 <dbl>, x_2_raw <dbl>, sd_1 <dbl>, sd_2 <dbl>,
## # sd_2_raw <dbl>, t <dbl>, d <dbl>, d_calc <dbl>, d_var_calc <dbl>,
## # es_method <chr>, unique_infant <chr>, test_method <chr>,
## # agent_argument_type_clean <chr>, patient_argument_type_clean <chr>,
## # adult_participant <chr>, data_source_clean <chr>Data Overview
n_effect_sizes <- ma_data %>%
filter(!is.na(d_calc)) %>%
nrow()
n_papers <- ma_data %>%
distinct(unique_id) %>%
nrow()There are 105 effect sizes collected from 30 different papers.
Here are the papers in this analysis:
ma_data %>%
count(short_cite) %>%
arrange(-n) %>%
DT::datatable()ma_model <- rma(ma_data$d_calc, ma_data$d_var_calc)
ma_model##
## Random-Effects Model (k = 105; tau^2 estimator: REML)
##
## tau^2 (estimated amount of total heterogeneity): 1.5214 (SE = 0.2340)
## tau (square root of estimated tau^2 value): 1.2335
## I^2 (total heterogeneity / total variability): 94.27%
## H^2 (total variability / sampling variability): 17.45
##
## Test for Heterogeneity:
## Q(df = 104) = 783.8714, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## 0.5523 0.1273 4.3383 <.0001 0.3028 0.8018 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1forest(ma_model,
header = T,
slab = ma_data$unique_id,
col = "red",
cex = .7)
#funnel plot {.tabset} ## vanilla
ma_data %>%
mutate(color = ifelse(sentence_structure == "transitive", "red", "blue"),
color_sample_size = ifelse(n_1 < 10, "red", ifelse(n_1 < 20, "orange", "yellow")),
color_confidence = ifelse(inclusion_certainty == 1, "red", "black"))-> ma_data_funnel
ma_data_funnel %>% filter (abs(d_calc) < 5) -> ma_data_funnel_no_outlier
ss_colors <- ma_data_funnel$color
ss_colors_no_outlier <- ma_data_funnel_no_outlier$color
ma_model_funnel <- rma(ma_data_funnel$d_calc, ma_data_funnel$d_var_calc)
ma_model_funnel_no_outlier <- rma(ma_data_funnel_no_outlier$d_calc, ma_data_funnel_no_outlier$d_var_calc)
f1<- funnel(ma_model_funnel, xlab = "Effect Size", col = ss_colors)
legend("topright",bg = "white",legend = c("transitive","intransitive"),pch=16,col=c("red", "blue"))
title(main = "All effect sizes break down by sentence structure")
f2<- funnel(ma_model_funnel_no_outlier, xlab = "Effect Size", col = ss_colors_no_outlier)
legend("topright",bg = "white",legend = c("transitive","intransitive"),pch=16,col=c("red", "blue"))
title(main = "effect sizes excluded outliers (abs <5) break down by sentence structure")
take int occount sentence structure?
ma_model_sentence_structure <- rma(ma_data_funnel$d_calc~ma_data_funnel$sentence_structure, ma_data_funnel$d_var_calc)
ma_model_no_outlier_ss <- rma(ma_data_funnel_no_outlier$d_calc~ma_data_funnel_no_outlier$sentence_structure, ma_data_funnel_no_outlier$d_var_calc)
f3 <- funnel(ma_model_sentence_structure, xlab = "effect size", col = ss_colors)
f3_b <- funnel(ma_model_no_outlier_ss, xlab = "effect size", col = ss_colors_no_outlier)
take int account sentence structure and age?
ma_model_ss_age <- rma(ma_data_funnel$d_calc~ma_data_funnel$sentence_structure + ma_data_funnel $mean_age, ma_data_funnel$d_var_calc)
ma_model_funnel_no_outlier_ss_age <- rma(ma_data_funnel_no_outlier$d_calc~ma_data_funnel_no_outlier$sentence_structure+ma_data_funnel_no_outlier$mean_age, ma_data_funnel_no_outlier$d_var_calc)
f4 <- funnel(ma_model_ss_age, xlab = "effect size", col = ss_colors)
f4_b <- funnel(ma_model_funnel_no_outlier_ss_age, xlab = "effect size", col = ss_colors_no_outlier)
Variable Summary
Continuous Variables
CONTINUOUS_VARS <- c("n_1", "x_1", "sd_1", "d_calc", "d_var_calc", "mean_age")
long_continuous <- ma_data %>%
pivot_longer(cols = CONTINUOUS_VARS)
long_continuous %>%
ggplot(aes(x = value)) +
geom_histogram() +
facet_wrap(~ name, scale = "free_x") +
labs(title = "Distribution of continuous measures")
long_continuous %>%
group_by(name) %>%
summarize(mean = mean(value),
sd = sd(value)) %>%
kable()| name | mean | sd |
|---|---|---|
| d_calc | 0.4640788 | 1.8999701 |
| d_var_calc | 0.2453866 | 0.5513378 |
| mean_age | 915.2242476 | 338.2881220 |
| n_1 | 15.4095238 | 5.9738134 |
| sd_1 | 0.1312320 | 0.0846320 |
| x_1 | 0.5557925 | 0.1121752 |
Categorical Variables
CATEGORICAL_VARS <- c("sentence_structure", "agent_argument_type", "patient_argument_type", "stimuli_actor",
"presentation_type", "character_identification",
"test_mass_or_distributed", "practice_phase", "test_method")
long_categorical <- ma_data %>%
pivot_longer(cols = CATEGORICAL_VARS) %>%
count(name, value) # this is a short cut for group_by() %>% summarize(count = n())
long_categorical %>%
ggplot(aes(x = value, y = n)) +
facet_wrap(~ name, scale = "free_x") +
geom_col(position = 'dodge',width=0.4) +
theme(text = element_text(size=8),
axis.text.x = element_text(angle = 90, hjust = 1)) # rotate x-axis text
Explore Moderators
no moderators
all
m1 <- rma.mv(d_calc, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m1)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -293.3322 586.6645 590.6645 595.9533 590.7833
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3820 0.6180 30 no short_cite
##
## Test for Heterogeneity:
## Q(df = 104) = 783.8714, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## 0.4296 0.1183 3.6319 0.0003 0.1978 0.6615 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<36
ma_data_young <- ma_data %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months < 36)
m_young <- rma.mv(d_calc, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young)
summary(m_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -202.6954 405.3909 409.3909 414.0258 409.5575
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4618 0.6796 23 no short_cite
##
## Test for Heterogeneity:
## Q(df = 75) = 570.7198, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## 0.3755 0.1479 2.5391 0.0111 0.0856 0.6654 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36
ma_data_old <- ma_data %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months > 36 | age_months == 36)
m_old <- rma.mv(d_calc, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -85.8581 171.7162 175.7162 178.3806 176.1962
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.1764 0.4200 8 no short_cite
##
## Test for Heterogeneity:
## Q(df = 28) = 206.4380, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## 0.6237 0.1650 3.7796 0.0002 0.3003 0.9472 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1age only
colored by unique_id
ma_data %>%
ggplot(aes(x = mean_age/30.44, y = d_calc,color = unique_id)) +
geom_point() +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (months)") 
all
ma_data %>%
ggplot(aes(x = mean_age/30.44, y = d_calc, size = n_1)) +
geom_point() +
geom_smooth(method = "lm") +
geom_smooth(color = "red") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (months)") +
theme(legend.position = "none") 
m_age <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -291.7567 583.5134 589.5134 597.4176 589.7558
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3869 0.6220 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 103) = 782.2682, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.7089, p-val = 0.1911
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1455 0.2479 0.5868 0.5573 -0.3404 0.6313
## mean_age 0.0003 0.0002 1.3073 0.1911 -0.0002 0.0008
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1forest(m_age,
header = T,
slab = ma_data$unique_id,
col = "red",
cex = .7
)
funnel(m_age)
young, < 36
ma_data_young %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1)) +
geom_point() +
geom_smooth(method = "lm") +
geom_smooth(color = "red") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") +
theme(legend.position = "none") 
m_age_young <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young)
summary(m_age_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -201.6933 403.3866 409.3866 416.2988 409.7295
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4673 0.6836 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 74) = 560.5676, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0680, p-val = 0.7943
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.5537 0.6991 0.7919 0.4284 -0.8166 1.9239
## mean_age -0.0002 0.0009 -0.2607 0.7943 -0.0020 0.0015
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1forest(m_age_young,
header = T,
slab = ma_data_young$unique_id,
col = "red",
cex = .7
)
old, >= 36
ma_data_old %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1)) +
geom_point() +
geom_smooth(method = "lm") +
geom_smooth(color = "red") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") +
theme(legend.position = "none") 
m_age_old <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -85.8085 171.6171 177.6171 181.5046 178.6606
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.1832 0.4280 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 206.4378, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.5825, p-val = 0.4453
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.3282 0.4232 0.7755 0.4381 -0.5013 1.1578
## mean_age 0.0002 0.0003 0.7632 0.4453 -0.0003 0.0008
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1age and test type
all
ma_data %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_method)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown my method") 
m_age_method <- rma.mv(d_calc ~ mean_age + test_method, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_method)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -290.9599 581.9197 589.9197 600.4196 590.3321
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3986 0.6313 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 780.7486, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.8068, p-val = 0.4052
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1492 0.2499 0.5969 0.5505 -0.3407 0.6391
## mean_age 0.0003 0.0003 1.0728 0.2834 -0.0002 0.0008
## test_methodpoint 0.0926 0.2963 0.3126 0.7545 -0.4881 0.6733
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1age and sentence structure
all
ma_data %>%
filter(sentence_structure != "bare_verb") %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, , color = sentence_structure)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") 
m_age_sentence <- rma.mv(d_calc ~ mean_age + sentence_structure, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_sentence)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -277.1705 554.3411 562.3411 572.8410 562.7534
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4433 0.6658 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 774.2955, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 31.1505, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt -0.1059 0.2592 -0.4085 0.6829 -0.6139
## mean_age 0.0003 0.0002 1.1396 0.2545 -0.0002
## sentence_structuretransitive 0.4331 0.0798 5.4259 <.0001 0.2767
## ci.ub
## intrcpt 0.4022
## mean_age 0.0008
## sentence_structuretransitive 0.5895 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Interaction:
m_age_sentence <- rma.mv(d_calc ~ mean_age * sentence_structure, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_sentence)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -272.2966 544.5932 554.5932 567.6688 555.2248
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4384 0.6621 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 101) = 761.9948, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 41.2039, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt 0.4127 0.3057 1.3498 0.1771
## mean_age -0.0003 0.0003 -1.0311 0.3025
## sentence_structuretransitive -0.2296 0.2233 -1.0283 0.3038
## mean_age:sentence_structuretransitive 0.0007 0.0002 3.1759 0.0015
## ci.lb ci.ub
## intrcpt -0.1865 1.0119
## mean_age -0.0009 0.0003
## sentence_structuretransitive -0.6673 0.2081
## mean_age:sentence_structuretransitive 0.0003 0.0012 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1< 36, young
ma_data_young_only <- ma_data %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months < 36)
ma_data_young_only %>%
filter(sentence_structure != "bare_verb") %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, , color = sentence_structure)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") 
m_age_sentence_young <- rma.mv(d_calc ~ mean_age + sentence_structure, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_sentence_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -197.4238 394.8475 402.8475 412.0094 403.4358
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.5015 0.7082 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 73) = 559.5013, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 8.6658, p-val = 0.0131
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.5518 0.7102 0.7769 0.4372 -0.8402
## mean_age -0.0004 0.0009 -0.4967 0.6194 -0.0022
## sentence_structuretransitive 0.2688 0.0916 2.9347 0.0033 0.0893
## ci.ub
## intrcpt 1.9438
## mean_age 0.0013
## sentence_structuretransitive 0.4483 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1interaction:
m_age_sentence_young <- rma.mv(d_calc ~ mean_age * sentence_structure, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_sentence_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -196.9600 393.9201 403.9201 415.3034 404.8292
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4942 0.7030 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 72) = 554.1432, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 9.7799, p-val = 0.0205
##
## Model Results:
##
## estimate se zval pval
## intrcpt 0.2327 0.7701 0.3022 0.7625
## mean_age -0.0000 0.0010 -0.0063 0.9949
## sentence_structuretransitive 0.7498 0.4622 1.6221 0.1048
## mean_age:sentence_structuretransitive -0.0007 0.0006 -1.0624 0.2881
## ci.lb ci.ub
## intrcpt -1.2766 1.7421
## mean_age -0.0019 0.0019
## sentence_structuretransitive -0.1562 1.6557
## mean_age:sentence_structuretransitive -0.0019 0.0006
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36, old
ma_data_old <- ma_data %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months > 36 | age_months == 36)
ma_data_old %>%
filter(sentence_structure != "bare_verb") %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = sentence_structure)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days)") 
m_age_sentence_old <- rma.mv(d_calc ~ mean_age + sentence_structure, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_sentence_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -68.8315 137.6630 145.6630 150.6954 147.5678
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.2999 0.5476 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 187.4101, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 35.2659, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt -0.4355 0.4625 -0.9416 0.3464 -1.3421
## mean_age 0.0003 0.0003 0.9103 0.3627 -0.0003
## sentence_structuretransitive 0.9653 0.1640 5.8854 <.0001 0.6438
## ci.ub
## intrcpt 0.4711
## mean_age 0.0008
## sentence_structuretransitive 1.2868 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1interaction
m_age_sentence_old <- rma.mv(d_calc ~ mean_age * sentence_structure, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_sentence_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -68.7597 137.5194 147.5194 153.6137 150.6773
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.2660 0.5158 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 175.6807, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 35.5003, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt 0.3053 1.1491 0.2657 0.7905
## mean_age -0.0003 0.0008 -0.3182 0.7503
## sentence_structuretransitive 0.1055 1.2385 0.0852 0.9321
## mean_age:sentence_structuretransitive 0.0006 0.0009 0.6936 0.4879
## ci.lb ci.ub
## intrcpt -1.9469 2.5576
## mean_age -0.0018 0.0013
## sentence_structuretransitive -2.3219 2.5329
## mean_age:sentence_structuretransitive -0.0011 0.0023
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1age with stimuli_actor
all
ma_data %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = stimuli_actor)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by stimuli_actor") 
m_age_stimuli_actor <- rma.mv(d_calc ~ mean_age + stimuli_actor, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
m_age_stimuli_actor_interaction <- rma.mv(d_calc ~ mean_age * stimuli_actor, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_stimuli_actor)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -290.5855 581.1710 589.1710 599.6709 589.5834
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3828 0.6187 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 764.8432, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 2.0931, p-val = 0.3511
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2385 0.2890 0.8253 0.4092 -0.3279 0.8050
## mean_age 0.0003 0.0002 1.2576 0.2085 -0.0002 0.0008
## stimuli_actorperson -0.1369 0.2208 -0.6198 0.5354 -0.5696 0.2959
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_stimuli_actor_interaction)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -288.4297 576.8595 586.8595 599.9351 587.4911
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4382 0.6620 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 101) = 764.4812, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 5.1449, p-val = 0.1615
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.5501 0.3512 1.5664 0.1173 -0.1382
## mean_age -0.0001 0.0003 -0.1968 0.8439 -0.0007
## stimuli_actorperson -0.8697 0.4810 -1.8081 0.0706 -1.8124
## mean_age:stimuli_actorperson 0.0009 0.0005 1.7805 0.0750 -0.0001
## ci.ub
## intrcpt 1.2385
## mean_age 0.0006
## stimuli_actorperson 0.0731 .
## mean_age:stimuli_actorperson 0.0018 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<36, young
ma_data_young_only %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = stimuli_actor)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by stimuli_actor, young only") 
m_age_stimuli_actor_young <- rma.mv(d_calc ~ mean_age + stimuli_actor, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_stimuli_actor_interaction_young <- rma.mv(d_calc ~ mean_age * stimuli_actor, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_stimuli_actor_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -200.7159 401.4317 409.4317 418.5935 410.0199
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4793 0.6923 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 73) = 552.6059, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.0974, p-val = 0.9525
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.5818 0.7268 0.8005 0.4234 -0.8427 2.0064
## mean_age -0.0002 0.0009 -0.2513 0.8016 -0.0020 0.0015
## stimuli_actorperson -0.0507 0.2715 -0.1868 0.8518 -0.5828 0.4814
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_stimuli_actor_interaction_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -199.6775 399.3549 409.3549 420.7383 410.2640
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.5075 0.7124 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 72) = 544.9146, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 0.2277, p-val = 0.9730
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.8661 1.0700 0.8095 0.4182 -1.2310
## mean_age -0.0006 0.0014 -0.4462 0.6554 -0.0034
## stimuli_actorperson -0.5866 1.4191 -0.4134 0.6793 -3.3681
## mean_age:stimuli_actorperson 0.0007 0.0019 0.3909 0.6959 -0.0029
## ci.ub
## intrcpt 2.9632
## mean_age 0.0021
## stimuli_actorperson 2.1949
## mean_age:stimuli_actorperson 0.0044
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36, old
ma_data_old %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = stimuli_actor)) +
geom_point() +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by stimuli_actor, old only") 
m_age_stimuli_actor_old <- rma.mv(d_calc ~ mean_age + stimuli_actor, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
m_age_stimuli_actor_interaction_old <- rma.mv(d_calc ~ mean_age * stimuli_actor, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_age_stimuli_actor_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -84.8371 169.6742 177.6742 182.7066 179.5790
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.1992 0.4463 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 204.0420, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.9935, p-val = 0.6085
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4278 0.4545 0.9412 0.3466 -0.4631 1.3186
## mean_age 0.0002 0.0003 0.7776 0.4368 -0.0003 0.0008
## stimuli_actorperson -0.2209 0.3482 -0.6345 0.5258 -0.9033 0.4615
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_stimuli_actor_interaction_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -83.5148 167.0297 177.0297 183.1240 180.1876
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.2964 0.5444 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 204.0071, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 4.2728, p-val = 0.2335
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.9892 0.5728 1.7269 0.0842 -0.1335
## mean_age -0.0002 0.0004 -0.5140 0.6073 -0.0009
## stimuli_actorperson -1.6965 0.9084 -1.8676 0.0618 -3.4769
## mean_age:stimuli_actorperson 0.0011 0.0006 1.8439 0.0652 -0.0001
## ci.ub
## intrcpt 2.1119 .
## mean_age 0.0005
## stimuli_actorperson 0.0839 .
## mean_age:stimuli_actorperson 0.0023 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1age with presentation_type
Decided to only compare asynchronous and immediate after:
ma_data %>%
count(presentation_type)## # A tibble: 3 x 2
## presentation_type n
## <chr> <int>
## 1 asynchronous 37
## 2 immediate_after 49
## 3 simultaneous 19ma_data_pt <- ma_data %>%
filter(presentation_type != "simultaneous")
ma_data_pt_young <- ma_data_pt %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months < 36)
ma_data_pt_old <- ma_data_pt %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months > 36 | age_months == 36) all
ma_data_pt %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = presentation_type)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by presentation type") 
m_age_pt <- rma.mv(d_calc ~ mean_age + presentation_type, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_pt)
m_age_pt_interaction <- rma.mv(d_calc ~ mean_age * presentation_type, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_pt)
summary(m_age_pt)##
## Multivariate Meta-Analysis Model (k = 86; method: REML)
##
## logLik Deviance AIC BIC AICc
## -215.4681 430.9363 438.9363 448.6116 439.4491
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4775 0.6910 20 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 83) = 579.8795, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.1224, p-val = 0.9406
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.4895 0.3154 1.5522 0.1206 -0.1286
## mean_age 0.0000 0.0003 0.0413 0.9671 -0.0006
## presentation_typeimmediate_after 0.0630 0.1887 0.3338 0.7385 -0.3068
## ci.ub
## intrcpt 1.1077
## mean_age 0.0006
## presentation_typeimmediate_after 0.4327
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_pt_interaction)##
## Multivariate Meta-Analysis Model (k = 86; method: REML)
##
## logLik Deviance AIC BIC AICc
## -214.0267 428.0533 438.0533 450.0869 438.8428
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4624 0.6800 20 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 82) = 571.1112, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 1.2903, p-val = 0.7314
##
## Model Results:
##
## estimate se zval pval
## intrcpt 1.3121 0.8299 1.5809 0.1139
## mean_age -0.0012 0.0012 -1.0205 0.3075
## presentation_typeimmediate_after -0.7348 0.7704 -0.9539 0.3401
## mean_age:presentation_typeimmediate_after 0.0012 0.0012 1.0731 0.2832
## ci.lb ci.ub
## intrcpt -0.3146 2.9387
## mean_age -0.0034 0.0011
## presentation_typeimmediate_after -2.2447 0.7750
## mean_age:presentation_typeimmediate_after -0.0010 0.0035
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<36, young
ma_data_pt_young %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = presentation_type)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by presentation type, young only") 
m_data_pt_young <- rma.mv(d_calc ~ mean_age + presentation_type, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_pt_young)
m_age_pt_interaction_young <- rma.mv(d_calc ~ mean_age * presentation_type, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_pt_young)
summary(m_age_pt)##
## Multivariate Meta-Analysis Model (k = 86; method: REML)
##
## logLik Deviance AIC BIC AICc
## -215.4681 430.9363 438.9363 448.6116 439.4491
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4775 0.6910 20 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 83) = 579.8795, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.1224, p-val = 0.9406
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.4895 0.3154 1.5522 0.1206 -0.1286
## mean_age 0.0000 0.0003 0.0413 0.9671 -0.0006
## presentation_typeimmediate_after 0.0630 0.1887 0.3338 0.7385 -0.3068
## ci.ub
## intrcpt 1.1077
## mean_age 0.0006
## presentation_typeimmediate_after 0.4327
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_pt_interaction)##
## Multivariate Meta-Analysis Model (k = 86; method: REML)
##
## logLik Deviance AIC BIC AICc
## -214.0267 428.0533 438.0533 450.0869 438.8428
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4624 0.6800 20 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 82) = 571.1112, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 1.2903, p-val = 0.7314
##
## Model Results:
##
## estimate se zval pval
## intrcpt 1.3121 0.8299 1.5809 0.1139
## mean_age -0.0012 0.0012 -1.0205 0.3075
## presentation_typeimmediate_after -0.7348 0.7704 -0.9539 0.3401
## mean_age:presentation_typeimmediate_after 0.0012 0.0012 1.0731 0.2832
## ci.lb ci.ub
## intrcpt -0.3146 2.9387
## mean_age -0.0034 0.0011
## presentation_typeimmediate_after -2.2447 0.7750
## mean_age:presentation_typeimmediate_after -0.0010 0.0035
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36, old
ma_data_pt_old %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = presentation_type)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by presentation type, young only") 
age with character_identification
all
ma_data %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = character_identification)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by character_identification") 
m_age_ci <- rma.mv(d_calc ~ mean_age + character_identification, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
m_age_stimuli_ci_interaction <- rma.mv(d_calc ~ mean_age * character_identification, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_ci)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -288.4414 576.8829 584.8829 595.3827 585.2952
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3801 0.6165 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 767.9935, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 6.6790, p-val = 0.0355
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0022 0.2552 0.0087 0.9930 -0.4980 0.5025
## mean_age 0.0002 0.0002 0.9841 0.3251 -0.0002 0.0007
## character_identificationyes 0.4330 0.1942 2.2294 0.0258 0.0523 0.8137
##
## intrcpt
## mean_age
## character_identificationyes *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_stimuli_ci_interaction)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -284.7699 569.5398 579.5398 592.6154 580.1714
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3935 0.6273 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 101) = 767.2829, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 12.7724, p-val = 0.0052
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.5587 0.3420 -1.6338 0.1023
## mean_age 0.0010 0.0004 2.5379 0.0112
## character_identificationyes 1.4183 0.4428 3.2033 0.0014
## mean_age:character_identificationyes -0.0012 0.0005 -2.4751 0.0133
## ci.lb ci.ub
## intrcpt -1.2289 0.1115
## mean_age 0.0002 0.0017 *
## character_identificationyes 0.5505 2.2861 **
## mean_age:character_identificationyes -0.0021 -0.0002 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<36, young
ma_data_young_only %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = character_identification)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by character_identification, young only") 
m_age_ci_young <- rma.mv(d_calc ~ mean_age + character_identification, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_ci_interaction_young <- rma.mv(d_calc ~ mean_age * character_identification, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_ci_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -197.9216 395.8431 403.8431 413.0050 404.4314
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4376 0.6616 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 73) = 531.1789, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 6.0267, p-val = 0.0491
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.5679 0.6887 0.8246 0.4096 -0.7820 1.9178
## mean_age -0.0005 0.0009 -0.6155 0.5382 -0.0023 0.0012
## character_identificationyes 0.5386 0.2209 2.4379 0.0148 0.1056 0.9717
##
## intrcpt
## mean_age
## character_identificationyes *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_ci_interaction_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -197.0208 394.0417 404.0417 415.4250 404.9507
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4322 0.6574 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 72) = 524.7532, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 6.2314, p-val = 0.1009
##
## Model Results:
##
## estimate se zval pval
## intrcpt 0.3388 0.8795 0.3852 0.7001
## mean_age -0.0002 0.0012 -0.1884 0.8506
## character_identificationyes 1.0724 1.2756 0.8406 0.4005
## mean_age:character_identificationyes -0.0007 0.0017 -0.4253 0.6706
## ci.lb ci.ub
## intrcpt -1.3849 2.0625
## mean_age -0.0025 0.0021
## character_identificationyes -1.4278 3.5725
## mean_age:character_identificationyes -0.0040 0.0026
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36, old
ma_data_old %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = character_identification)) +
geom_point() +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by character_identification, old only") 
age with practice_phase
all
ma_data %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = practice_phase)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by practice_phase") 
m_age_pf <- rma.mv(d_calc ~ mean_age + character_identification, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
m_age_pf_interaction <- rma.mv(d_calc ~ mean_age * character_identification, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_ci)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -288.4414 576.8829 584.8829 595.3827 585.2952
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3801 0.6165 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 767.9935, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 6.6790, p-val = 0.0355
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0022 0.2552 0.0087 0.9930 -0.4980 0.5025
## mean_age 0.0002 0.0002 0.9841 0.3251 -0.0002 0.0007
## character_identificationyes 0.4330 0.1942 2.2294 0.0258 0.0523 0.8137
##
## intrcpt
## mean_age
## character_identificationyes *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_stimuli_ci_interaction)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -284.7699 569.5398 579.5398 592.6154 580.1714
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3935 0.6273 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 101) = 767.2829, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 12.7724, p-val = 0.0052
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.5587 0.3420 -1.6338 0.1023
## mean_age 0.0010 0.0004 2.5379 0.0112
## character_identificationyes 1.4183 0.4428 3.2033 0.0014
## mean_age:character_identificationyes -0.0012 0.0005 -2.4751 0.0133
## ci.lb ci.ub
## intrcpt -1.2289 0.1115
## mean_age 0.0002 0.0017 *
## character_identificationyes 0.5505 2.2861 **
## mean_age:character_identificationyes -0.0021 -0.0002 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<36, young
ma_data_young_only %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = practice_phase)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by practice_phase, young only") 
m_age_pf_young <- rma.mv(d_calc ~ mean_age + practice_phase, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_pf_interaction_young <- rma.mv(d_calc ~ mean_age * practice_phase, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_pf_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -200.5617 401.1234 409.1234 418.2852 409.7116
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4238 0.6510 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 73) = 535.9618, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.2744, p-val = 0.5288
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.7018 0.6931 1.0126 0.3113 -0.6566 2.0603
## mean_age -0.0005 0.0009 -0.5842 0.5591 -0.0023 0.0012
## practice_phaseyes 0.1817 0.1671 1.0875 0.2768 -0.1458 0.5093
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_pf_interaction_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -198.9942 397.9885 407.9885 419.3718 408.8976
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4555 0.6749 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 72) = 530.7942, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.8556, p-val = 0.4144
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 1.2301 0.8193 1.5014 0.1332 -0.3757 2.8359
## mean_age -0.0013 0.0011 -1.1944 0.2323 -0.0035 0.0009
## practice_phaseyes -1.1221 0.9964 -1.1261 0.2601 -3.0751 0.8309
## mean_age:practice_phaseyes 0.0019 0.0014 1.3181 0.1875 -0.0009 0.0047
##
## intrcpt
## mean_age
## practice_phaseyes
## mean_age:practice_phaseyes
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36, old
ma_data_old %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = practice_phase)) +
geom_point() +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by practice_phase, old only") 
age with test_mass_or_distributed
all
ma_data %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_mass_or_distributed)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by test type") 
m_age_tt <- rma.mv(d_calc ~ mean_age + test_mass_or_distributed, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
m_age_tt_interaction <- rma.mv(d_calc ~ mean_age * test_mass_or_distributed, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_age_tt)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -290.1523 580.3047 588.3047 598.8046 588.7170
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3870 0.6221 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 769.1828, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 2.7628, p-val = 0.2512
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0394 0.2686 0.1466 0.8834 -0.4870 0.5658
## mean_age 0.0003 0.0002 1.4389 0.1502 -0.0001 0.0008
## test_mass_or_distributedmass 0.2793 0.2720 1.0266 0.3046 -0.2539 0.8124
##
## intrcpt
## mean_age
## test_mass_or_distributedmass
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_tt_interaction)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -288.1692 576.3383 586.3383 599.4139 586.9699
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3734 0.6111 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 101) = 755.6914, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 5.0953, p-val = 0.1649
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.0811 0.2782 -0.2915 0.7707
## mean_age 0.0005 0.0003 1.8617 0.0626
## test_mass_or_distributedmass 1.2284 0.6808 1.8043 0.0712
## mean_age:test_mass_or_distributedmass -0.0012 0.0008 -1.5166 0.1294
## ci.lb ci.ub
## intrcpt -0.6263 0.4641
## mean_age -0.0000 0.0010 .
## test_mass_or_distributedmass -0.1060 2.5629 .
## mean_age:test_mass_or_distributedmass -0.0027 0.0003
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<36, young
ma_data_young_only %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_mass_or_distributed)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by test_mass_or_distributed, young only") 
m_age_tt_young <- rma.mv(d_calc ~ mean_age + test_mass_or_distributed, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
m_age_tt_interaction_young <- rma.mv(d_calc ~ mean_age * test_mass_or_distributed, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young_only)
summary(m_age_tt_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -199.7548 399.5096 407.5096 416.6715 408.0979
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4574 0.6763 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 73) = 548.4824, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.6835, p-val = 0.4310
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1770 0.7580 0.2335 0.8154 -1.3087 1.6627
## mean_age 0.0001 0.0009 0.0979 0.9221 -0.0017 0.0019
## test_mass_or_distributedmass 0.4228 0.3331 1.2692 0.2044 -0.2301 1.0757
##
## intrcpt
## mean_age
## test_mass_or_distributedmass
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_age_tt_interaction_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -198.4770 396.9539 406.9539 418.3373 407.8630
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4784 0.6917 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 72) = 548.4171, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.4680, p-val = 0.4811
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.5423 1.0886 -0.4982 0.6184
## mean_age 0.0010 0.0013 0.7375 0.4608
## test_mass_or_distributedmass 1.7117 1.4382 1.1901 0.2340
## mean_age:test_mass_or_distributedmass -0.0017 0.0019 -0.9216 0.3567
## ci.lb ci.ub
## intrcpt -2.6759 1.5913
## mean_age -0.0016 0.0036
## test_mass_or_distributedmass -1.1072 4.5305
## mean_age:test_mass_or_distributedmass -0.0053 0.0019
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>= 36, old
ma_data_old %>%
mutate(age_months = mean_age/30.44) %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1, color = test_mass_or_distributed)) +
geom_point() +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (days), breakdown by test_mass_or_distributed, old only") 
repetition only
repetition only
ma_data %>%
ggplot(mapping = aes(x = n_repetitions_sentence, y = d_calc)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("number of repetition per novel verb") +
ggtitle("Syntactical Bootstrapping effect size vs. number of repetitions for verb") +
theme_classic() +
theme(legend.position = "none")
m_rep <- rma.mv(d_calc ~ n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_rep)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -292.6018 585.2036 591.2036 599.1078 591.4460
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3900 0.6245 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 103) = 782.9687, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0174, p-val = 0.8949
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4162 0.1574 2.6436 0.0082 0.1076 0.7248 **
## n_repetitions_sentence 0.0018 0.0137 0.1321 0.8949 -0.0251 0.0287
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1repetition only, young
ma_data_young %>%
ggplot(mapping = aes(x = n_repetitions_sentence, y = d_calc)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("number of repetition per novel verb") +
ggtitle("Syntactical Bootstrapping effect size vs. number of repetitions for verb") +
theme_classic() +
theme(legend.position = "none")
m_rep_young <- rma.mv(d_calc ~ n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young)
summary(m_rep_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -201.9811 403.9621 409.9621 416.8743 410.3050
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4736 0.6882 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 74) = 570.5964, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1498, p-val = 0.6987
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.3249 0.1990 1.6329 0.1025 -0.0651 0.7149
## n_repetitions_sentence 0.0057 0.0148 0.3870 0.6987 -0.0232 0.0347
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1repetition only, old
ma_data_old %>%
ggplot(mapping = aes(x = n_repetitions_sentence, y = d_calc)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("number of repetition per novel verb") +
ggtitle("Syntactical Bootstrapping effect size vs. number of repetitions for verb") +
theme_classic() +
theme(legend.position = "none")
m_rep_old <- rma.mv(d_calc ~ n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_rep_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -84.5965 169.1930 175.1930 179.0805 176.2365
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.1846 0.4297 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 205.4444, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.9520, p-val = 0.3292
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.3077 0.3662 0.8402 0.4008 -0.4100 1.0254
## n_repetitions_sentence 0.0929 0.0952 0.9757 0.3292 -0.0937 0.2796
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1repetition with age
correlation
all
m_rep_age <- rma.mv(d_calc ~ mean_age + n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
m_rep_age_interaction <- rma.mv(d_calc ~ mean_age*n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data)
summary(m_rep_age)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -291.0774 582.1548 590.1548 600.6547 590.5671
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3973 0.6303 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 102) = 782.1754, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.9251, p-val = 0.3819
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0703 0.2961 0.2373 0.8124 -0.5101 0.6506
## mean_age 0.0003 0.0002 1.3805 0.1674 -0.0001 0.0008
## n_repetitions_sentence 0.0066 0.0142 0.4649 0.6420 -0.0212 0.0343
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_rep_age_interaction)##
## Multivariate Meta-Analysis Model (k = 105; method: REML)
##
## logLik Deviance AIC BIC AICc
## -290.1825 580.3649 590.3649 603.4405 590.9965
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.3964 0.6296 30 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 101) = 774.7436, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.1813, p-val = 0.5356
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 0.0025 0.3250 0.0077 0.9939 -0.6344
## mean_age 0.0005 0.0004 1.3224 0.1860 -0.0002
## n_repetitions_sentence 0.0305 0.0493 0.6188 0.5361 -0.0661
## mean_age:n_repetitions_sentence -0.0000 0.0001 -0.5067 0.6124 -0.0002
## ci.ub
## intrcpt 0.6394
## mean_age 0.0012
## n_repetitions_sentence 0.1270
## mean_age:n_repetitions_sentence 0.0001
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1young, <36
m_rep_age_young <- rma.mv(d_calc ~ mean_age + n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young)
m_rep_age_interaction_young <- rma.mv(d_calc ~ mean_age*n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_young)
summary(m_rep_age_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -200.9924 401.9848 409.9848 419.1467 410.5731
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4840 0.6957 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 73) = 559.8183, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 0.1628, p-val = 0.9218
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4037 0.8317 0.4854 0.6274 -1.2264 2.0338
## mean_age -0.0001 0.0010 -0.0984 0.9216 -0.0020 0.0018
## n_repetitions_sentence 0.0052 0.0161 0.3199 0.7490 -0.0265 0.0368
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_rep_age_interaction_young)##
## Multivariate Meta-Analysis Model (k = 76; method: REML)
##
## logLik Deviance AIC BIC AICc
## -199.8017 399.6033 409.6033 420.9867 410.5124
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.4986 0.7061 23 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 72) = 559.6199, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 1.3065, p-val = 0.7276
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt -0.4403 1.1428 -0.3853 0.7000 -2.6802
## mean_age 0.0011 0.0015 0.7530 0.4514 -0.0018
## n_repetitions_sentence 0.0811 0.0727 1.1157 0.2646 -0.0614
## mean_age:n_repetitions_sentence -0.0001 0.0001 -1.0687 0.2852 -0.0003
## ci.ub
## intrcpt 1.7995
## mean_age 0.0040
## n_repetitions_sentence 0.2236
## mean_age:n_repetitions_sentence 0.0001
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1old > 36
m_rep_age_old <- rma.mv(d_calc ~ mean_age + n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
m_rep_age_interaction_old <- rma.mv(d_calc ~ mean_age*n_repetitions_sentence , V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_old)
summary(m_rep_age_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -84.5529 169.1058 177.1058 182.1382 179.0106
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.1936 0.4400 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 205.4251, p-val < .0001
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 1.5081, p-val = 0.4705
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0145 0.5364 0.0270 0.9785 -1.0369 1.0658
## mean_age 0.0002 0.0003 0.7578 0.4486 -0.0003 0.0008
## n_repetitions_sentence 0.0926 0.0966 0.9592 0.3375 -0.0966 0.2819
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(m_rep_age_interaction_old)##
## Multivariate Meta-Analysis Model (k = 29; method: REML)
##
## logLik Deviance AIC BIC AICc
## -83.4154 166.8308 176.8308 182.9252 179.9887
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.2205 0.4695 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 198.5403, p-val < .0001
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 2.2824, p-val = 0.5159
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt 4.2809 4.7873 0.8942 0.3712 -5.1019
## mean_age -0.0034 0.0041 -0.8415 0.4001 -0.0114
## n_repetitions_sentence -1.3422 1.6008 -0.8384 0.4018 -4.4798
## mean_age:n_repetitions_sentence 0.0012 0.0013 0.8988 0.3688 -0.0014
## ci.ub
## intrcpt 13.6638
## mean_age 0.0045
## n_repetitions_sentence 1.7954
## mean_age:n_repetitions_sentence 0.0038
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1vocab
vocab (median)
ma_data_with_vocab <- ma_data %>%
mutate(vocab = case_when(!is.na(productive_vocab_median) ~ productive_vocab_median,
!is.na(productive_vocab_mean) ~ productive_vocab_mean,
TRUE ~ NA_real_),
vocab_source = case_when(!is.na(productive_vocab_median) ~ "median",
!is.na(productive_vocab_mean) ~ "mean",
TRUE ~ NA_character_))
ma_data_with_vocab %>%
ggplot(aes(x = productive_vocab_median, y = d_calc)) +
geom_point() +
geom_smooth(method = "lm") +
theme_classic()
m_vocab <- rma.mv(d_calc ~ productive_vocab_median, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_with_vocab)
summary(m_vocab)##
## Multivariate Meta-Analysis Model (k = 40; method: REML)
##
## logLik Deviance AIC BIC AICc
## -90.7783 181.5566 187.5566 192.4694 188.2625
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.7075 0.8412 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.3051, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0401, p-val = 0.8413
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.7831 0.4339 1.8050 0.0711 -0.0672 1.6335 .
## productive_vocab_median -0.0014 0.0068 -0.2003 0.8413 -0.0148 0.0120
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1age comparison
ma_data_with_vocab_age <- ma_data_with_vocab %>%
filter(vocab_source == "median" &
!is.na(vocab))
ma_data_with_vocab_age %>%
ggplot(aes(x = mean_age, y = d_calc)) +
geom_point() +
geom_smooth(method = "lm") +
theme_classic()
m_age_with_vocab <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_with_vocab_age)
summary(m_age_with_vocab)##
## Multivariate Meta-Analysis Model (k = 40; method: REML)
##
## logLik Deviance AIC BIC AICc
## -90.4576 180.9152 186.9152 191.8279 187.6211
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.7145 0.8453 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.4185, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3462, p-val = 0.5563
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 1.2707 0.9825 1.2933 0.1959 -0.6550 3.1964
## mean_age -0.0008 0.0013 -0.5884 0.5563 -0.0034 0.0018
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1< 36, young
ma_data_with_vocab_age_young <- ma_data_with_vocab_age %>%
mutate(age_months = mean_age/30.44) %>%
filter(age_months < 36)
ma_data_with_vocab_age_young %>%
ggplot(aes(x = productive_vocab_median, y = d_calc, size = n_1)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. vocab (months)") 
m_age_with_vocab_young <- rma.mv(d_calc ~ productive_vocab_median, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_with_vocab_age_young)
summary(m_age_with_vocab_young)##
## Multivariate Meta-Analysis Model (k = 40; method: REML)
##
## logLik Deviance AIC BIC AICc
## -90.7783 181.5566 187.5566 192.4694 188.2625
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.7075 0.8412 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.3051, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0401, p-val = 0.8413
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.7831 0.4339 1.8050 0.0711 -0.0672 1.6335 .
## productive_vocab_median -0.0014 0.0068 -0.2003 0.8413 -0.0148 0.0120
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1< 36, young, age comparison
ma_data_with_vocab_age_young %>%
ggplot(aes(x = age_months, y = d_calc, size = n_1)) +
geom_point() +
geom_smooth(method = "lm") +
ylab("Effect Size") +
xlab("Age (days)") +
ggtitle("Syntactical Bootstrapping effect size vs. Age (months)") 
m_age_with_vocab_young <- rma.mv(d_calc ~ mean_age, V = d_var_calc,
random = ~ 1 | short_cite, data = ma_data_with_vocab_age_young)
summary(m_age_with_vocab)##
## Multivariate Meta-Analysis Model (k = 40; method: REML)
##
## logLik Deviance AIC BIC AICc
## -90.4576 180.9152 186.9152 191.8279 187.6211
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2 0.7145 0.8453 8 no short_cite
##
## Test for Residual Heterogeneity:
## QE(df = 38) = 251.4185, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3462, p-val = 0.5563
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 1.2707 0.9825 1.2933 0.1959 -0.6550 3.1964
## mean_age -0.0008 0.0013 -0.5884 0.5563 -0.0034 0.0018
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1correlationt est
cor.test(ma_data_with_vocab$mean_age,
ma_data_with_vocab$productive_vocab_median)##
## Pearson's product-moment correlation
##
## data: ma_data_with_vocab$mean_age and ma_data_with_vocab$productive_vocab_median
## t = 12.979, df = 38, p-value = 1.532e-15
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.8235024 0.9480383
## sample estimates:
## cor
## 0.9032915contingency table
ALL_CATEGORICAL_VARS <- c("test_type","presentation_type",
"agent_argument_type_clean", "patient_argument_type_clean",
"stimuli_modality", "stimuli_actor", "character_identification", "practice_phase", "test_mass_or_distributed", "test_method")
get_cross_counts <- function(args, df){
var1 = args[[1]]
var2 = args[[2]]
if (var1 != var2){
df %>%
select_(var1, var2) %>%
rename(v1 = var1,
v2 = var2) %>%
count(v1, v2) %>%
mutate(v1_long = glue("{var1}/{v1}"),
v2_long = glue("{var2}/{v2}")) %>%
select(v1_long, v2_long, n)
}
}
all_pair_counts <- list(ALL_CATEGORICAL_VARS,
ALL_CATEGORICAL_VARS) %>%
cross() %>%
map_df(get_cross_counts, ma_data) %>%
complete(v1_long, v2_long, fill = list(n = 0)) %>%
filter(v1_long != v2_long)
all_counts_wide <- all_pair_counts %>%
pivot_wider(names_from = v2_long, values_from = n)
all_counts_wide_matrix <- all_counts_wide %>%
select(-v1_long) %>%
as.matrix()
row.names(all_counts_wide_matrix) <- all_counts_wide$v1_long
heatmaply(all_counts_wide_matrix,
fontsize_row = 8,
fontsize_col = 8)Model selections??
http://www.metafor-project.org/doku.php/tips:model_selection_with_glmulti_and_mumin
eval(metafor:::.MuMIn)
ma_data## # A tibble: 105 x 55
## x1 coder unique_id link grammatical_cla… paper_eligibili… short_cite
## <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 1 alan… arunacha… http… verb include Arunachal…
## 2 2 alan… arunacha… http… verb include Arunachal…
## 3 3 alan… arunacha… http… verb include Arunachal…
## 4 4 alan… arunacha… http… verb include Arunachal…
## 5 5 alan… arunacha… http… verb include Arunachal…
## 6 6 anjie arunacha… http… verb include Arunachal…
## 7 7 anjie arunacha… http… verb include Arunachal…
## 8 8 alan… bunger20… http… verb include Bunger, A…
## 9 9 alan… bunger20… http… verb include Bunger, A…
## 10 10 alan… bunger20… http… verb include Bunger, A…
## # … with 95 more rows, and 48 more variables: data_source <chr>,
## # expt_num <chr>, expt_condition <chr>, dependent_measure <chr>,
## # test_type <chr>, same_infant <chr>, language <chr>, mean_age <dbl>,
## # productive_vocab_mean <dbl>, productive_vocab_median <dbl>,
## # population_type <chr>, sentence_structure <chr>, agent_argument_type <chr>,
## # patient_argument_type <chr>, verb_type <chr>, stimuli_type <chr>,
## # stimuli_modality <chr>, stimuli_actor <chr>, presentation_type <chr>,
## # character_identification <chr>, practice_phase <chr>,
## # test_mass_or_distributed <chr>, n_train_test_pair <dbl>,
## # n_test_trial_per_pair <dbl>, n_repetitions_sentence <dbl>,
## # n_repetitions_video <dbl>, example_target_sentence <chr>,
## # test_question <chr>, inclusion_certainty <dbl>, note <chr>, n_1 <dbl>,
## # x_1 <dbl>, x_2 <dbl>, x_2_raw <dbl>, sd_1 <dbl>, sd_2 <dbl>,
## # sd_2_raw <dbl>, t <dbl>, d <dbl>, d_calc <dbl>, d_var_calc <dbl>,
## # es_method <chr>, unique_infant <chr>, test_method <chr>,
## # agent_argument_type_clean <chr>, patient_argument_type_clean <chr>,
## # adult_participant <chr>, data_source_clean <chr>full <- rma.mv(d_calc, d_var_calc, mods = ~ mean_age + agent_argument_type_clean + patient_argument_type_clean + stimuli_modality + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video + test_method,
data=ma_data, method="ML")
res <- dredge(full, trace=2)##
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|======================================================================| 100%subset(res, delta <= 2, recalc.weights=FALSE)## Global model call: rma.mv(yi = d_calc, V = d_var_calc, mods = ~mean_age + agent_argument_type_clean +
## patient_argument_type_clean + stimuli_modality + stimuli_actor +
## presentation_type + test_mass_or_distributed + practice_phase +
## character_identification + n_repetitions_sentence + n_repetitions_video +
## test_method, data = ma_data, method = "ML")
## ---
## Model selection table
## (Int) agn_arg_typ_cln chr_idn n_rpt_snt n_rpt_vid ptn_arg_typ_cln prc_phs
## 4028 + + + 0.02482 -0.1557 +
## 4026 + + 0.02037 -0.1422 +
## 4090 + + 0.02110 -0.1083 + +
## 1980 + + + 0.02196 -0.1757 +
## prs_typ stm_act stm_mdl tst_mss_or_dst tst_mth df logLik AICc delta
## 4028 + + + + + 17 -292.796 626.6 0.00
## 4026 + + + + + 16 -294.767 627.7 1.09
## 4090 + + + + + 17 -293.488 628.0 1.38
## 1980 + + + + 16 -294.968 628.1 1.49
## weight
## 4028 0.166
## 4026 0.096
## 4090 0.083
## 1980 0.079
## Models ranked by AICc(x)model selection
take everything
rma.glmulti <- function(formula,data)
{rma.mv(formula, d_var_calc, data=ma_data, method="ML")
}
res_sink <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video + test_method, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
##
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 725.864818541665
##
## After 100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 715.577293551161
##
## After 150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Crit= 685.621375640315
## Mean crit= 702.934590573398
##
## After 200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Crit= 681.908005574812
## Mean crit= 692.58121918037
##
## After 250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Crit= 679.326562070076
## Mean crit= 685.66494209925
##
## After 300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Crit= 675.615212139058
## Mean crit= 683.087299477267
##
## After 350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type
## Crit= 675.615212139058
## Mean crit= 681.041840284071
##
## After 400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Crit= 658.04629132771
## Mean crit= 674.609490842962
##
## After 450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Crit= 658.04629132771
## Mean crit= 668.472326568765
##
## After 500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 654.840389646851
## Mean crit= 661.80051897223
##
## After 550 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181##
## After 600 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181
##
## After 650 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181##
## After 700 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181##
## After 750 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 657.53210059181##
## After 800 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 656.348270487966##
## After 850 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 656.348270487966
##
## After 900 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 656.348270487966##
## After 950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed+practice_phase
## Crit= 643.215901075392
## Mean crit= 652.239304622212##
## After 1000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed+practice_phase
## Crit= 643.215901075392
## Mean crit= 652.239304622212
##
## After 1050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 649.217817133762
##
## After 1100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953##
## After 1150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953
##
## After 1200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953##
## After 1250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953##
## After 1300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953##
## After 1350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953##
## After 1400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.953333503953##
## After 1450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.80098079723##
## After 1500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.80098079723
##
## After 1550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.774535022456
##
## After 1600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 1650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648
##
## After 1700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 1750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 1800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 1850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 1900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 1950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.752245435648##
## After 2000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 644.161601224252##
## After 2050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 644.161601224252
##
## After 2100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 643.526880484051
##
## After 2150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535
##
## After 2250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186697415535##
## After 2650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 2700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926
##
## After 2750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 2800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 2850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 2900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 2950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 3000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.186209426926##
## After 3050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.137366768907##
## After 3100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.137366768907
##
## After 3150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 642.137366768907##
## After 3200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163
##
## After 3300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 3950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 4000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 4050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 4100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 4150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 4200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 640.066057793163##
## After 4250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546
##
## After 4350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 639.106001301546##
## After 4750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 637.74342984342
##
## After 4800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 4850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134
##
## After 4900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 4950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 636.845202940134##
## After 5300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783
##
## After 5400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.12514647783##
## After 5850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 5900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095
##
## After 5950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.882753691095##
## After 6350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.412208996814
##
## After 6400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827
##
## After 6500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.347303736827##
## After 6900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 6950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752
##
## After 7000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 632.322724864752##
## After 7400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.8141873625
##
## After 7450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969
##
## After 7550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 631.729289660969##
## After 7950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062
##
## After 8050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.987130067062##
## After 8500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256
##
## After 8600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 8950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 9950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 10950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.798876135256##
## After 11650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 11700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738
##
## After 11750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 11800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 11850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 11900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 11950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 12950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 13000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 13050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 13100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 13150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 13200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.795179549738##
## After 13250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337
##
## After 13350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.587859656337##
## After 13800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 13850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383
##
## After 13900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 13950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.482508470383##
## After 14300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049
##
## After 14400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 14950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 630.395236385049##
## After 15350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 627.714907756343
## Mean crit= 630.098068933114
##
## After 15400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788
##
## After 15500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.657544045788##
## After 15900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 15950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907
##
## After 16000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.337227851907##
## After 16400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 629.171128087261
##
## After 16450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912
##
## After 16550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.725621543912##
## After 16950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_sentence+n_repetitions_video+test_method
## Crit= 626.162713518951
## Mean crit= 628.594452184632
## Completed.print(res_sink)## glmulti.analysis
## Method: h / Fitting: rma.glmulti / IC used: aicc
## Level: 1 / Marginality: FALSE
## From 32 models:
## Best IC: 626.162713518951
## Best model:
## [1] "d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + "
## [2] " test_type + stimuli_actor + stimuli_modality + presentation_type + "
## [3] " test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + "
## [4] " test_method"
## Evidence weight: 0.0868908971237817
## Worst IC: 629.815123421915
## 12 models within 2 IC units.
## 28 models to reach 95% of evidence weight.top <- weightable(res_sink)
top <- top[top$aicc <= min(top$aicc) + 2,]
top## model
## 1 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 2 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 3 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 4 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 5 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 6 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video + test_method
## 7 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 8 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + n_repetitions_sentence + n_repetitions_video + test_method
## 9 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video + test_method
## 10 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video + test_method
## 11 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## 12 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## aicc weights
## 1 626.1627 0.08689090
## 2 626.1627 0.08689090
## 3 626.6273 0.06887925
## 4 626.6273 0.06887925
## 5 626.8462 0.06173869
## 6 626.8462 0.06173869
## 7 627.7149 0.03998707
## 8 627.7149 0.03998707
## 9 628.0097 0.03450715
## 10 628.0097 0.03450715
## 11 628.1178 0.03269093
## 12 628.1178 0.03269093summary(res_sink@objects[[1]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -292.5641 609.3440 619.1282 664.2456 626.1627
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 88) = 609.3440, p-val < .0001
##
## Test of Moderators (coefficients 2:17):
## QM(df = 16) = 174.5274, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.3715 0.2437 -1.5247 0.1273
## agent_argument_type_cleannoun_phrase -0.0294 0.1515 -0.1940 0.8462
## agent_argument_type_cleanpronoun -1.1277 0.1863 -6.0544 <.0001
## agent_argument_type_cleanvarying_agent 0.2101 0.1700 1.2360 0.2165
## patient_argument_type_cleannoun -0.1101 0.1027 -1.0720 0.2837
## patient_argument_type_cleannoun_phrase 0.9547 0.1547 6.1722 <.0001
## patient_argument_type_cleanpronoun 1.0107 0.1461 6.9186 <.0001
## patient_argument_type_cleanvarying_patient -0.6173 0.1658 -3.7225 0.0002
## test_typeagent -0.4712 0.2245 -2.0988 0.0358
## stimuli_actorperson -0.7062 0.1255 -5.6266 <.0001
## stimuli_modalityvideo 1.0359 0.1535 6.7497 <.0001
## presentation_typeimmediate_after 0.8181 0.1958 4.1784 <.0001
## presentation_typesimultaneous 0.4582 0.1925 2.3797 0.0173
## test_mass_or_distributedmass 0.5228 0.1174 4.4544 <.0001
## n_repetitions_sentence 0.0273 0.0099 2.7607 0.0058
## n_repetitions_video -0.1337 0.0358 -3.7316 0.0002
## test_methodpoint 0.3894 0.1397 2.7870 0.0053
## ci.lb ci.ub
## intrcpt -0.8491 0.1061
## agent_argument_type_cleannoun_phrase -0.3262 0.2675
## agent_argument_type_cleanpronoun -1.4928 -0.7626 ***
## agent_argument_type_cleanvarying_agent -0.1231 0.5434
## patient_argument_type_cleannoun -0.3114 0.0912
## patient_argument_type_cleannoun_phrase 0.6515 1.2579 ***
## patient_argument_type_cleanpronoun 0.7244 1.2970 ***
## patient_argument_type_cleanvarying_patient -0.9423 -0.2923 ***
## test_typeagent -0.9112 -0.0312 *
## stimuli_actorperson -0.9522 -0.4602 ***
## stimuli_modalityvideo 0.7351 1.3367 ***
## presentation_typeimmediate_after 0.4344 1.2018 ***
## presentation_typesimultaneous 0.0808 0.8355 *
## test_mass_or_distributedmass 0.2928 0.7529 ***
## n_repetitions_sentence 0.0079 0.0466 **
## n_repetitions_video -0.2039 -0.0635 ***
## test_methodpoint 0.1156 0.6633 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_sink, type="s")
summary(res_sink@objects[[2]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -292.5641 609.3440 619.1282 664.2456 626.1627
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 88) = 609.3440, p-val < .0001
##
## Test of Moderators (coefficients 2:17):
## QM(df = 16) = 174.5274, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.3715 0.2437 -1.5247 0.1273
## sentence_structuretransitive -0.6173 0.1658 -3.7225 0.0002
## agent_argument_type_cleannoun_phrase -0.0294 0.1515 -0.1940 0.8462
## agent_argument_type_cleanpronoun -1.1277 0.1863 -6.0544 <.0001
## agent_argument_type_cleanvarying_agent 0.2101 0.1700 1.2360 0.2165
## patient_argument_type_cleannoun 0.5072 0.1594 3.1829 0.0015
## patient_argument_type_cleannoun_phrase 1.5720 0.2259 6.9581 <.0001
## patient_argument_type_cleanpronoun 1.6280 0.2195 7.4154 <.0001
## test_typeagent -0.4712 0.2245 -2.0988 0.0358
## stimuli_actorperson -0.7062 0.1255 -5.6266 <.0001
## stimuli_modalityvideo 1.0359 0.1535 6.7497 <.0001
## presentation_typeimmediate_after 0.8181 0.1958 4.1784 <.0001
## presentation_typesimultaneous 0.4582 0.1925 2.3797 0.0173
## test_mass_or_distributedmass 0.5228 0.1174 4.4544 <.0001
## n_repetitions_sentence 0.0273 0.0099 2.7607 0.0058
## n_repetitions_video -0.1337 0.0358 -3.7316 0.0002
## test_methodpoint 0.3894 0.1397 2.7870 0.0053
## ci.lb ci.ub
## intrcpt -0.8491 0.1061
## sentence_structuretransitive -0.9423 -0.2923 ***
## agent_argument_type_cleannoun_phrase -0.3262 0.2675
## agent_argument_type_cleanpronoun -1.4928 -0.7626 ***
## agent_argument_type_cleanvarying_agent -0.1231 0.5434
## patient_argument_type_cleannoun 0.1949 0.8195 **
## patient_argument_type_cleannoun_phrase 1.1292 2.0148 ***
## patient_argument_type_cleanpronoun 1.1977 2.0583 ***
## test_typeagent -0.9112 -0.0312 *
## stimuli_actorperson -0.9522 -0.4602 ***
## stimuli_modalityvideo 0.7351 1.3367 ***
## presentation_typeimmediate_after 0.4344 1.2018 ***
## presentation_typesimultaneous 0.0808 0.8355 *
## test_mass_or_distributedmass 0.2928 0.7529 ***
## n_repetitions_sentence 0.0079 0.0466 **
## n_repetitions_video -0.2039 -0.0635 ***
## test_methodpoint 0.1156 0.6633 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_sink, type="s")
eval(metafor:::.glmulti)
coef(res_sink)## Estimate Uncond. variance
## mean_age -5.717145e-06 7.855875e-10
## practice_phaseyes 3.076182e-02 3.846448e-03
## test_typeagent -1.973216e-01 6.627146e-02
## sentence_structuretransitive -3.244215e-01 1.192952e-01
## patient_argument_type_cleanvarying_patient -3.244215e-01 1.192952e-01
## character_identificationyes 9.760541e-02 1.392176e-02
## test_methodpoint 2.845269e-01 3.135633e-02
## n_repetitions_sentence 2.438700e-02 1.133115e-04
## intrcpt -3.214126e-01 6.976540e-02
## agent_argument_type_cleannoun_phrase -3.280362e-02 2.323232e-02
## agent_argument_type_cleanpronoun -1.128194e+00 3.643199e-02
## agent_argument_type_cleanvarying_agent 2.277545e-01 3.180320e-02
## patient_argument_type_cleannoun 2.018958e-01 1.236271e-01
## patient_argument_type_cleannoun_phrase 1.306063e+00 1.428847e-01
## patient_argument_type_cleanpronoun 1.346457e+00 1.415696e-01
## stimuli_actorperson -6.824526e-01 1.817586e-02
## stimuli_modalityvideo 1.013606e+00 2.449866e-02
## presentation_typeimmediate_after 7.555101e-01 4.135693e-02
## presentation_typesimultaneous 4.619675e-01 4.063332e-02
## test_mass_or_distributedmass 5.048201e-01 1.570356e-02
## n_repetitions_video -1.419722e-01 1.682711e-03
## Nb models Importance
## mean_age 6 0.1059877
## practice_phaseyes 12 0.2541233
## test_typeagent 14 0.4753094
## sentence_structuretransitive 16 0.5000000
## patient_argument_type_cleanvarying_patient 16 0.5000000
## character_identificationyes 18 0.5298367
## test_methodpoint 24 0.8436815
## n_repetitions_sentence 30 0.9705281
## intrcpt 32 1.0000000
## agent_argument_type_cleannoun_phrase 32 1.0000000
## agent_argument_type_cleanpronoun 32 1.0000000
## agent_argument_type_cleanvarying_agent 32 1.0000000
## patient_argument_type_cleannoun 32 1.0000000
## patient_argument_type_cleannoun_phrase 32 1.0000000
## patient_argument_type_cleanpronoun 32 1.0000000
## stimuli_actorperson 32 1.0000000
## stimuli_modalityvideo 32 1.0000000
## presentation_typeimmediate_after 32 1.0000000
## presentation_typesimultaneous 32 1.0000000
## test_mass_or_distributedmass 32 1.0000000
## n_repetitions_video 32 1.0000000
## +/- (alpha=0.05)
## mean_age 5.493452e-05
## practice_phaseyes 1.215565e-01
## test_typeagent 5.045583e-01
## sentence_structuretransitive 6.769546e-01
## patient_argument_type_cleanvarying_patient 6.769546e-01
## character_identificationyes 2.312572e-01
## test_methodpoint 3.470649e-01
## n_repetitions_sentence 2.086340e-02
## intrcpt 5.176881e-01
## agent_argument_type_cleannoun_phrase 2.987407e-01
## agent_argument_type_cleanpronoun 3.741016e-01
## agent_argument_type_cleanvarying_agent 3.495293e-01
## patient_argument_type_cleannoun 6.891359e-01
## patient_argument_type_cleannoun_phrase 7.408682e-01
## patient_argument_type_cleanpronoun 7.374509e-01
## stimuli_actorperson 2.642382e-01
## stimuli_modalityvideo 3.067745e-01
## presentation_typeimmediate_after 3.985862e-01
## presentation_typesimultaneous 3.950838e-01
## test_mass_or_distributedmass 2.456106e-01
## n_repetitions_video 8.039940e-02mmi <- as.data.frame(coef(res_sink))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)## Estimate Std. Error z value Pr(>|z|)
## intrcpt -0.3214 0.2641 -1.2169 0.2237
## agent_argument_type_cleannoun_phrase -0.0328 0.1524 -0.2152 0.8296
## agent_argument_type_cleanpronoun -1.1282 0.1909 -5.9107 0.0000
## agent_argument_type_cleanvarying_agent 0.2278 0.1783 1.2771 0.2016
## patient_argument_type_cleannoun 0.2019 0.3516 0.5742 0.5658
## patient_argument_type_cleannoun_phrase 1.3061 0.3780 3.4552 0.0005
## patient_argument_type_cleanpronoun 1.3465 0.3763 3.5786 0.0003
## stimuli_actorperson -0.6825 0.1348 -5.0620 0.0000
## stimuli_modalityvideo 1.0136 0.1565 6.4759 0.0000
## presentation_typeimmediate_after 0.7555 0.2034 3.7151 0.0002
## presentation_typesimultaneous 0.4620 0.2016 2.2918 0.0219
## test_mass_or_distributedmass 0.5048 0.1253 4.0284 0.0001
## n_repetitions_video -0.1420 0.0410 -3.4610 0.0005
## n_repetitions_sentence 0.0244 0.0106 2.2910 0.0220
## test_methodpoint 0.2845 0.1771 1.6068 0.1081
## character_identificationyes 0.0976 0.1180 0.8272 0.4081
## patient_argument_type_cleanvarying_patient -0.3244 0.3454 -0.9393 0.3476
## sentence_structuretransitive -0.3244 0.3454 -0.9393 0.3476
## test_typeagent -0.1973 0.2574 -0.7665 0.4434
## practice_phaseyes 0.0308 0.0620 0.4960 0.6199
## mean_age 0.0000 0.0000 -0.2040 0.8384
## ci.lb ci.ub Importance
## intrcpt -0.8391 0.1963 1.0000
## agent_argument_type_cleannoun_phrase -0.3315 0.2659 1.0000
## agent_argument_type_cleanpronoun -1.5023 -0.7541 1.0000
## agent_argument_type_cleanvarying_agent -0.1218 0.5773 1.0000
## patient_argument_type_cleannoun -0.4872 0.8910 1.0000
## patient_argument_type_cleannoun_phrase 0.5652 2.0469 1.0000
## patient_argument_type_cleanpronoun 0.6090 2.0839 1.0000
## stimuli_actorperson -0.9467 -0.4182 1.0000
## stimuli_modalityvideo 0.7068 1.3204 1.0000
## presentation_typeimmediate_after 0.3569 1.1541 1.0000
## presentation_typesimultaneous 0.0669 0.8571 1.0000
## test_mass_or_distributedmass 0.2592 0.7504 1.0000
## n_repetitions_video -0.2224 -0.0616 1.0000
## n_repetitions_sentence 0.0035 0.0453 0.9705
## test_methodpoint -0.0625 0.6316 0.8437
## character_identificationyes -0.1337 0.3289 0.5298
## patient_argument_type_cleanvarying_patient -1.0014 0.3525 0.5000
## sentence_structuretransitive -1.0014 0.3525 0.5000
## test_typeagent -0.7019 0.3072 0.4753
## practice_phaseyes -0.0908 0.1523 0.2541
## mean_age -0.0001 0.0000 0.1060three interdependence moderators, take one ### take test type
rma.glmulti <- function(formula,data)
{rma.mv(formula, d_var_calc, data=ma_data, method="ML")
}
res_test_type <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
##
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 725.864818541665
##
## After 100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Crit= 681.908005574812
## Mean crit= 705.533482683937
##
## After 150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type
## Crit= 681.908005574812
## Mean crit= 693.779782457757
##
## After 200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Crit= 676.702282084101
## Mean crit= 684.228322412755
##
## After 250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 675.534339426318
##
## After 300 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 673.113846675074
##
## After 350 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 672.687365995921
##
## After 400 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 671.779309026182
##
## After 450 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 671.108211728166
##
## After 500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 667.553576499284
##
## After 550 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617##
## After 600 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617
##
## After 650 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617##
## After 700 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.834678393617##
## After 750 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.3524303454
##
## After 800 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803##
## After 850 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803
##
## After 900 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803##
## After 950 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803##
## After 1000 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 664.140017201803##
## After 1050 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253##
## After 1100 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253
##
## After 1150 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253##
## After 1200 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253##
## After 1250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.708633923253##
## After 1300 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.269476446531
##
## After 1350 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677##
## After 1400 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677
##
## After 1450 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677##
## After 1500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.222770491677##
## After 1550 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.123555700273
##
## After 1600 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487##
## After 1650 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487
##
## After 1700 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487##
## After 1750 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487##
## After 1800 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+test_type+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.608879610229
## Mean crit= 663.032359962487##
## After 1850 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779##
## After 1900 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779
##
## After 1950 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779##
## After 2000 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779##
## After 2050 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.628196577779##
## After 2100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.307531708463
##
## After 2150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567
##
## After 2250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 2950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 3950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 4000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 4050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 4100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 4150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 4200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567##
## After 4250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.281850994567## Completed.print(res_test_type)## glmulti.analysis
## Method: h / Fitting: rma.glmulti / IC used: aicc
## Level: 1 / Marginality: FALSE
## From 32 models:
## Best IC: 660.894852560475
## Best model:
## [1] "d_calc ~ 1 + sentence_structure + agent_argument_type_clean + "
## [2] " patient_argument_type_clean + presentation_type + test_mass_or_distributed + "
## [3] " practice_phase + character_identification + n_repetitions_sentence"
## [1] "d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + "
## [2] " presentation_type + test_mass_or_distributed + practice_phase + "
## [3] " character_identification + n_repetitions_sentence"
## Evidence weight: 0.0598302838054941
## Worst IC: 663.015244221681
## 28 models within 2 IC units.
## 29 models to reach 95% of evidence weight.top <- weightable(res_test_type)
top <- top[top$aicc <= min(top$aicc) + 2,]
top## model
## 1 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 2 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 3 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 4 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 5 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 6 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 7 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 8 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 9 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 10 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 11 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 12 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 13 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 14 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 15 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 16 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 17 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 18 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 19 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 20 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 21 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 22 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 23 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 24 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 25 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## 26 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## 27 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 28 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + test_type + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## aicc weights
## 1 660.8949 0.05983028
## 2 660.8949 0.05983028
## 3 661.5400 0.04333476
## 4 661.5400 0.04333476
## 5 661.6089 0.04186702
## 6 661.6089 0.04186702
## 7 661.7956 0.03813436
## 8 661.7956 0.03813436
## 9 662.0483 0.03360882
## 10 662.0483 0.03360882
## 11 662.0817 0.03305251
## 12 662.0817 0.03305251
## 13 662.3370 0.02909195
## 14 662.3370 0.02909195
## 15 662.3376 0.02908232
## 16 662.3376 0.02908232
## 17 662.3737 0.02856237
## 18 662.3737 0.02856237
## 19 662.5565 0.02606714
## 20 662.5565 0.02606714
## 21 662.5650 0.02595685
## 22 662.5650 0.02595685
## 23 662.6773 0.02454008
## 24 662.6773 0.02454008
## 25 662.8049 0.02302266
## 26 662.8049 0.02302266
## 27 662.8900 0.02206418
## 28 662.8900 0.02206418summary(res_test_type@objects[[1]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -314.1141 652.4440 656.2282 693.3836 660.8949
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
##
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.4006 0.1987 -2.0164 0.0438
## sentence_structuretransitive -0.4510 0.1667 -2.7055 0.0068
## agent_argument_type_cleannoun_phrase 0.1634 0.1458 1.1203 0.2626
## agent_argument_type_cleanpronoun -0.9581 0.1605 -5.9689 <.0001
## agent_argument_type_cleanvarying_agent 0.2469 0.1580 1.5625 0.1182
## patient_argument_type_cleannoun 0.3665 0.1592 2.3028 0.0213
## patient_argument_type_cleannoun_phrase 1.4053 0.2104 6.6800 <.0001
## patient_argument_type_cleanpronoun 1.5518 0.2273 6.8285 <.0001
## presentation_typeimmediate_after 0.6529 0.1696 3.8486 0.0001
## presentation_typesimultaneous 0.4518 0.1678 2.6928 0.0071
## test_mass_or_distributedmass 0.3585 0.1009 3.5538 0.0004
## practice_phaseyes 0.1489 0.0762 1.9545 0.0506
## character_identificationyes 0.2226 0.0903 2.4638 0.0137
## n_repetitions_sentence 0.0190 0.0094 2.0272 0.0426
## ci.lb ci.ub
## intrcpt -0.7900 -0.0112 *
## sentence_structuretransitive -0.7778 -0.1243 **
## agent_argument_type_cleannoun_phrase -0.1224 0.4491
## agent_argument_type_cleanpronoun -1.2727 -0.6435 ***
## agent_argument_type_cleanvarying_agent -0.0628 0.5567
## patient_argument_type_cleannoun 0.0546 0.6784 *
## patient_argument_type_cleannoun_phrase 0.9929 1.8176 ***
## patient_argument_type_cleanpronoun 1.1064 1.9972 ***
## presentation_typeimmediate_after 0.3204 0.9854 ***
## presentation_typesimultaneous 0.1230 0.7807 **
## test_mass_or_distributedmass 0.1608 0.5562 ***
## practice_phaseyes -0.0004 0.2982 .
## character_identificationyes 0.0455 0.3996 *
## n_repetitions_sentence 0.0006 0.0373 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_test_type, type="s")
summary(res_test_type@objects[[2]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -314.1141 652.4440 656.2282 693.3836 660.8949
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
##
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.4006 0.1987 -2.0164 0.0438
## agent_argument_type_cleannoun_phrase 0.1634 0.1458 1.1203 0.2626
## agent_argument_type_cleanpronoun -0.9581 0.1605 -5.9689 <.0001
## agent_argument_type_cleanvarying_agent 0.2469 0.1580 1.5625 0.1182
## patient_argument_type_cleannoun -0.0846 0.1016 -0.8323 0.4053
## patient_argument_type_cleannoun_phrase 0.9542 0.1402 6.8057 <.0001
## patient_argument_type_cleanpronoun 1.1007 0.1458 7.5518 <.0001
## patient_argument_type_cleanvarying_patient -0.4510 0.1667 -2.7055 0.0068
## presentation_typeimmediate_after 0.6529 0.1696 3.8486 0.0001
## presentation_typesimultaneous 0.4518 0.1678 2.6928 0.0071
## test_mass_or_distributedmass 0.3585 0.1009 3.5538 0.0004
## practice_phaseyes 0.1489 0.0762 1.9545 0.0506
## character_identificationyes 0.2226 0.0903 2.4638 0.0137
## n_repetitions_sentence 0.0190 0.0094 2.0272 0.0426
## ci.lb ci.ub
## intrcpt -0.7900 -0.0112 *
## agent_argument_type_cleannoun_phrase -0.1224 0.4491
## agent_argument_type_cleanpronoun -1.2727 -0.6435 ***
## agent_argument_type_cleanvarying_agent -0.0628 0.5567
## patient_argument_type_cleannoun -0.2837 0.1146
## patient_argument_type_cleannoun_phrase 0.6794 1.2290 ***
## patient_argument_type_cleanpronoun 0.8151 1.3864 ***
## patient_argument_type_cleanvarying_patient -0.7778 -0.1243 **
## presentation_typeimmediate_after 0.3204 0.9854 ***
## presentation_typesimultaneous 0.1230 0.7807 **
## test_mass_or_distributedmass 0.1608 0.5562 ***
## practice_phaseyes -0.0004 0.2982 .
## character_identificationyes 0.0455 0.3996 *
## n_repetitions_sentence 0.0006 0.0373 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_test_type, type="s")
eval(metafor:::.glmulti)
coef(res_test_type)## Estimate Uncond. variance
## stimuli_actorperson -0.0121306928 6.330089e-04
## test_typeagent -0.0748860964 1.855515e-02
## practice_phaseyes 0.0620099120 7.223407e-03
## patient_argument_type_cleanvarying_patient -0.2043327785 5.474697e-02
## sentence_structuretransitive -0.2043327785 5.474697e-02
## mean_age 0.0001747588 4.378124e-08
## character_identificationyes 0.1302965213 1.404469e-02
## n_repetitions_sentence 0.0144090061 1.337974e-04
## intrcpt -0.4076971546 8.206490e-02
## agent_argument_type_cleannoun_phrase 0.2002873402 2.148478e-02
## agent_argument_type_cleanpronoun -0.9798212355 3.259569e-02
## agent_argument_type_cleanvarying_agent 0.2048524412 2.644506e-02
## patient_argument_type_cleannoun 0.1217250140 5.937123e-02
## patient_argument_type_cleannoun_phrase 1.1291984096 7.458725e-02
## patient_argument_type_cleanpronoun 1.3065595657 7.755690e-02
## presentation_typeimmediate_after 0.6395098876 3.864976e-02
## presentation_typesimultaneous 0.3569413462 3.371999e-02
## test_mass_or_distributedmass 0.4186360679 1.295125e-02
## Nb models Importance
## stimuli_actorperson 4 0.09358327
## test_typeagent 8 0.23690084
## practice_phaseyes 14 0.43072200
## patient_argument_type_cleanvarying_patient 16 0.50000000
## sentence_structuretransitive 16 0.50000000
## mean_age 16 0.51928651
## character_identificationyes 22 0.69128421
## n_repetitions_sentence 22 0.75403675
## intrcpt 32 1.00000000
## agent_argument_type_cleannoun_phrase 32 1.00000000
## agent_argument_type_cleanpronoun 32 1.00000000
## agent_argument_type_cleanvarying_agent 32 1.00000000
## patient_argument_type_cleannoun 32 1.00000000
## patient_argument_type_cleannoun_phrase 32 1.00000000
## patient_argument_type_cleanpronoun 32 1.00000000
## presentation_typeimmediate_after 32 1.00000000
## presentation_typesimultaneous 32 1.00000000
## test_mass_or_distributedmass 32 1.00000000
## +/- (alpha=0.05)
## stimuli_actorperson 0.0493120431
## test_typeagent 0.2669809582
## practice_phaseyes 0.1665785725
## patient_argument_type_cleanvarying_patient 0.4585937428
## sentence_structuretransitive 0.4585937428
## mean_age 0.0004101022
## character_identificationyes 0.2322759075
## n_repetitions_sentence 0.0226710690
## intrcpt 0.5614703338
## agent_argument_type_cleannoun_phrase 0.2872853853
## agent_argument_type_cleanpronoun 0.3538573248
## agent_argument_type_cleanvarying_agent 0.3187280829
## patient_argument_type_cleannoun 0.4775689864
## patient_argument_type_cleannoun_phrase 0.5352792343
## patient_argument_type_cleanpronoun 0.5458311269
## presentation_typeimmediate_after 0.3853199390
## presentation_typesimultaneous 0.3599082704
## test_mass_or_distributedmass 0.2230509126mmi <- as.data.frame(coef(res_test_type))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)## Estimate Std. Error z value Pr(>|z|)
## intrcpt -0.4077 0.2865 -1.4232 0.1547
## agent_argument_type_cleannoun_phrase 0.2003 0.1466 1.3664 0.1718
## agent_argument_type_cleanpronoun -0.9798 0.1805 -5.4271 0.0000
## agent_argument_type_cleanvarying_agent 0.2049 0.1626 1.2597 0.2078
## patient_argument_type_cleannoun 0.1217 0.2437 0.4996 0.6174
## patient_argument_type_cleannoun_phrase 1.1292 0.2731 4.1346 0.0000
## patient_argument_type_cleanpronoun 1.3066 0.2785 4.6916 0.0000
## presentation_typeimmediate_after 0.6395 0.1966 3.2529 0.0011
## presentation_typesimultaneous 0.3569 0.1836 1.9438 0.0519
## test_mass_or_distributedmass 0.4186 0.1138 3.6786 0.0002
## n_repetitions_sentence 0.0144 0.0116 1.2457 0.2129
## character_identificationyes 0.1303 0.1185 1.0995 0.2716
## mean_age 0.0002 0.0002 0.8352 0.4036
## sentence_structuretransitive -0.2043 0.2340 -0.8733 0.3825
## patient_argument_type_cleanvarying_patient -0.2043 0.2340 -0.8733 0.3825
## practice_phaseyes 0.0620 0.0850 0.7296 0.4656
## test_typeagent -0.0749 0.1362 -0.5498 0.5825
## stimuli_actorperson -0.0121 0.0252 -0.4821 0.6297
## ci.lb ci.ub Importance
## intrcpt -0.9692 0.1538 1.0000
## agent_argument_type_cleannoun_phrase -0.0870 0.4876 1.0000
## agent_argument_type_cleanpronoun -1.3337 -0.6260 1.0000
## agent_argument_type_cleanvarying_agent -0.1139 0.5236 1.0000
## patient_argument_type_cleannoun -0.3558 0.5993 1.0000
## patient_argument_type_cleannoun_phrase 0.5939 1.6645 1.0000
## patient_argument_type_cleanpronoun 0.7607 1.8524 1.0000
## presentation_typeimmediate_after 0.2542 1.0248 1.0000
## presentation_typesimultaneous -0.0030 0.7168 1.0000
## test_mass_or_distributedmass 0.1956 0.6417 1.0000
## n_repetitions_sentence -0.0083 0.0371 0.7540
## character_identificationyes -0.1020 0.3626 0.6913
## mean_age -0.0002 0.0006 0.5193
## sentence_structuretransitive -0.6629 0.2543 0.5000
## patient_argument_type_cleanvarying_patient -0.6629 0.2543 0.5000
## practice_phaseyes -0.1046 0.2286 0.4307
## test_typeagent -0.3419 0.1921 0.2369
## stimuli_actorperson -0.0614 0.0372 0.0936take test method
res_test_method <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video + test_method, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
##
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Crit= 685.621375640315
## Mean crit= 719.578802019467
##
## After 100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+test_mass_or_distributed
## Crit= 676.702282084101
## Mean crit= 698.307675972734
##
## After 150 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 685.05876444974
##
## After 200 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 678.263457220778
##
## After 250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 673.743174119515
##
## After 300 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 670.987070822418
##
## After 350 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 669.438547847758
##
## After 400 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 665.399129492211##
## After 450 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 665.399129492211
##
## After 500 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 665.121127961905
##
## After 550 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.989147048741##
## After 600 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed
## Crit= 662.336953435415
## Mean crit= 663.989147048741
##
## After 650 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.696878763114
##
## After 700 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.609770449294##
## After 750 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.609770449294
##
## After 800 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.250100017641##
## After 850 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.250100017641
##
## After 900 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+n_repetitions_sentence
## Crit= 661.795645116288
## Mean crit= 663.250100017641##
## After 950 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.95501513407##
## After 1000 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence
## Crit= 661.539966286458
## Mean crit= 662.95501513407
##
## After 1050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.64582515669
##
## After 1100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973
##
## After 1200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 1950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.564788971973##
## After 2000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642
##
## After 2100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 2950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 3000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.548510884642##
## After 3050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.510679707891##
## After 3100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.510679707891
##
## After 3150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.510679707891##
## After 3200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882
##
## After 3300 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3350 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3400 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3450 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3550 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3600 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3650 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3700 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 3950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 4000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 4050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 4100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 4150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 4200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882##
## After 4250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type+test_mass_or_distributed+practice_phase+character_identification+n_repetitions_sentence
## Crit= 660.894852560475
## Mean crit= 662.50227818882## Completed.print(res)## Global model call: rma.mv(yi = d_calc, V = d_var_calc, mods = ~mean_age + agent_argument_type_clean +
## patient_argument_type_clean + stimuli_modality + stimuli_actor +
## presentation_type + test_mass_or_distributed + practice_phase +
## character_identification + n_repetitions_sentence + n_repetitions_video +
## test_method, data = ma_data, method = "ML")
## ---
## Model selection table
## (Int) agn_arg_typ_cln chr_idn men_age n_rpt_snt n_rpt_vid
## 4028 + + + 2.482e-02 -1.557e-01
## 4026 + + 2.037e-02 -1.422e-01
## 4090 + + 2.110e-02 -1.083e-01
## 1980 + + + 2.196e-02 -1.757e-01
## 4092 + + + 2.443e-02 -1.322e-01
## 4032 + + + -6.528e-05 2.476e-02 -1.582e-01
## 2044 + + + 2.166e-02 -1.446e-01
## 2042 + + 1.755e-02 -1.181e-01
## 4018 + + -1.402e-01
## 4082 + + -1.086e-01
## 4030 + + 9.070e-05 2.086e-02 -1.399e-01
## 4020 + + + -1.493e-01
## 1984 + + + 1.257e-04 2.250e-02 -1.680e-01
## 2034 + + -1.167e-01
## 1972 + + + -1.667e-01
## 4094 + + 9.039e-06 2.114e-02 -1.083e-01
## 1978 + + 1.600e-02 -1.632e-01
## 1982 + + 2.699e-04 1.881e-02 -1.500e-01
## 1970 + + -1.587e-01
## 4096 + + + -9.424e-05 2.431e-02 -1.341e-01
## 2046 + + 1.798e-04 1.916e-02 -1.168e-01
## 2036 + + + -1.340e-01
## 4074 + + 2.118e-02
## 4084 + + + -1.230e-01
## 2048 + + + 8.919e-05 2.207e-02 -1.414e-01
## 4022 + + 4.295e-05 -1.391e-01
## 1974 + + 2.049e-04 -1.481e-01
## 2038 + + 1.164e-04 -1.158e-01
## 4086 + + -3.697e-05 -1.084e-01
## 4024 + + + -7.645e-05 -1.522e-01
## 1976 + + + 8.849e-05 -1.611e-01
## 4066 + +
## 4076 + + + 2.211e-02
## 2040 + + + 4.932e-05 -1.322e-01
## 4078 + + -2.502e-06 2.117e-02
## 4088 + + + -1.089e-04 -1.253e-01
## 2026 + + 1.710e-02
## 3896 + + + -3.662e-04 -1.411e-01
## 2018 + +
## 3960 + + + -3.991e-04 -1.100e-01
## 2030 + + 1.956e-04 1.886e-02
## 3904 + + + -3.599e-04 1.036e-02 -1.309e-01
## 4070 + + -4.858e-05
## 4068 + + +
## 3892 + + + -1.278e-01
## 4080 + + + -3.214e-05 2.206e-02
## 2028 + + + 1.840e-02
## 3968 + + + -3.936e-04 1.070e-02 -9.859e-02
## 2022 + + 1.330e-04
## 3900 + + + 1.081e-02 -1.175e-01
## 2020 + + +
## 3958 + + -3.513e-04 -7.368e-02
## 3956 + + + -1.029e-01
## 2032 + + + 1.801e-04 1.937e-02
## 1844 + + + -1.350e-01
## 3964 + + + 1.110e-02 -9.120e-02
## 4072 + + + -4.922e-05
## 1908 + + + -1.003e-01
## 3942 + + -3.401e-04
## 3954 + + -7.132e-02
## 3952 + + + -3.594e-04 1.459e-02
## 2024 + + + 1.396e-04
## 3950 + + -3.314e-04 1.083e-02
## 4010 + + 1.944e-02
## 3966 + + -3.440e-04 7.079e-03 -6.339e-02
## 956 + + + 3.340e-02 -1.998e-01
## 3944 + + + -3.616e-04
## 3938 + +
## 1020 + + + 3.258e-02 -1.579e-01
## 3890 + + -1.088e-01
## 1912 + + + -1.734e-04 -1.027e-01
## 1848 + + + -1.186e-04 -1.405e-01
## 3946 + + 1.131e-02
## 3894 + + -2.707e-04 -1.164e-01
## 3962 + + 7.772e-03 -6.007e-02
## 3948 + + + 1.470e-02
## 1852 + + + 3.135e-03 -1.325e-01
## 4012 + + + 2.202e-02
## 1018 + + 2.831e-02 -1.293e-01
## 4002 + +
## 1916 + + + 4.282e-03 -9.552e-02
## 4014 + + 1.907e-04 2.049e-02
## 1906 + + -6.356e-02
## 3940 + + +
## 1890 + +
## 960 + + + -1.418e-04 3.194e-02 -2.067e-01
## 1024 + + + -1.809e-04 3.064e-02 -1.629e-01
## 3898 + + 5.905e-03 -1.019e-01
## 1892 + + +
## 3004 + + + 3.310e-02 -2.004e-01
## 3902 + + -2.631e-04 5.115e-03 -1.103e-01
## 1920 + + + -1.619e-04 2.850e-03 -9.935e-02
## 1856 + + + -1.098e-04 2.061e-03 -1.384e-01
## 3068 + + + 3.203e-02 -1.587e-01
## 4006 + + 1.432e-04
## 4016 + + + 1.263e-04 2.223e-02
## 4004 + + +
## 1022 + + -7.428e-05 2.721e-02 -1.294e-01
## 1910 + + -1.098e-04 -6.314e-02
## 3066 + + 2.811e-02 -1.295e-01
## 1894 + + -1.141e-04
## 1900 + + + 7.749e-03
## 1914 + + 4.205e-04 -6.287e-02
## 1898 + + 3.983e-03
## 1896 + + + -1.518e-04
## 954 + + 2.721e-02 -1.868e-01
## 3008 + + + -1.871e-04 3.271e-02 -2.063e-01
## 3072 + + + -2.290e-04 3.145e-02 -1.624e-01
## 1966 + + 4.372e-04 1.775e-02
## 1958 + + 3.737e-04
## 4008 + + + 1.097e-04
## 1842 + + -1.134e-01
## 1904 + + + -1.263e-04 6.740e-03
## 1918 + + -1.133e-04 -7.283e-04 -6.431e-02
## 3070 + + -9.630e-05 2.757e-02 -1.288e-01
## 1902 + + -9.941e-05 3.047e-03
## 1724 + + + 2.436e-02 -9.189e-02
## 3884 + + + 1.715e-02
## 958 + + 3.672e-05 2.778e-02 -1.854e-01
## 1968 + + + 3.909e-04 1.908e-02
## 3002 + + 2.773e-02 -1.859e-01
## 1728 + + + 2.269e-04 2.526e-02 -8.047e-02
## 3888 + + + -2.298e-04 1.733e-02
## 1002 + + 2.842e-02
## 1960 + + + 3.499e-04
## 1850 + + -3.580e-03 -1.172e-01
## 1954 + +
## 3772 + + + 2.547e-02 -8.128e-02
## 1010 + + -1.299e-01
## 1846 + + 1.805e-05 -1.128e-01
## 1788 + + + 2.437e-02 -9.598e-02
## 1962 + + 1.278e-02
## 3876 + + +
## 1964 + + + 1.667e-02
## 3882 + + 1.245e-02
## 1956 + + +
## 1014 + + -2.104e-04 -1.300e-01
## 3874 + +
## 3006 + + 2.942e-05 2.790e-02 -1.852e-01
## 3880 + + + -2.232e-04
## 1016 + + + -2.989e-04 -1.541e-01
## 3058 + + -1.324e-01
## 1716 + + + -7.945e-02
## 1004 + + + 2.980e-02
## 1792 + + + 2.352e-04 2.533e-02 -8.967e-02
## 1012 + + + -1.444e-01
## 3776 + + + 2.032e-04 2.563e-02 -7.728e-02
## 1006 + + -7.191e-05 2.736e-02
## 948 + + + -1.918e-01
## 3050 + + 2.879e-02
## 1854 + + -2.290e-06 -3.609e-03 -1.173e-01
## 3886 + + -1.693e-04 1.229e-02
## 952 + + + -2.588e-04 -2.051e-01
## 3878 + + -1.755e-04
## 3836 + + + 2.558e-02 -8.925e-02
## 1772 + + + 2.180e-02
## 1712 + + + 3.662e-04 2.212e-02
## 946 + + -1.837e-01
## 3060 + + + -1.500e-01
## 1710 + + 4.796e-04 1.943e-02
## 3756 + + + 2.359e-02
## 1726 + + 4.400e-04 2.028e-02 -4.725e-02
## 1776 + + + 2.803e-04 2.315e-02
## 1720 + + + 1.886e-04 -6.957e-02
## 2996 + + + -1.984e-01
## 3062 + + -1.688e-04 -1.311e-01
## 1774 + + 4.095e-04 2.019e-02
## 3820 + + + 2.387e-02
## 1008 + + + -1.091e-04 2.858e-02
## 3764 + + + -7.422e-02
## 3760 + + + 2.590e-04 2.391e-02
## 1708 + + + 1.973e-02
## 3064 + + + -2.678e-04 -1.546e-01
## 1780 + + + -8.260e-02
## 3052 + + + 3.007e-02
## 3840 + + + 2.086e-04 2.577e-02 -8.733e-02
## 3054 + + -1.185e-04 2.811e-02
## 1702 + + 4.116e-04
## 1828 + + +
## 2994 + + -1.876e-01
## 950 + + -9.900e-05 -1.877e-01
## 1718 + + 3.722e-04 -4.372e-02
## 3000 + + + -2.208e-04 -2.054e-01
## 3758 + + 4.257e-04 2.026e-02
## 1764 + + +
## 1704 + + + 3.153e-04
## 3824 + + + 2.260e-04 2.412e-02
## 1790 + + 4.217e-04 2.039e-02 -3.746e-02
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## 2 + +
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## 1 +
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## 513 +
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## 602 + + -1.595e-03 6.605e-02
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## 5 + 1.066e-04
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## 93 + -1.371e-05 -3.063e-03 1.074e-02
## 2054 + + 3.121e-05
## 94 + + -2.525e-05 -4.218e-03 3.931e-02
## 2138 + + -4.307e-03 3.856e-02
## 582 + + 1.114e-05
## 2073 + -2.021e-03 -8.655e-03
## 2626 + +
## 2134 + + -1.110e-05 4.538e-02
## 2069 + -2.172e-05 -4.664e-03
## 2061 + -3.548e-05 -9.866e-04
## 537 + -5.222e-03 -1.268e-02
## 525 + 6.052e-05 -2.521e-03
## 533 + 8.053e-05 -4.761e-03
## 538 + + -4.286e-03 1.260e-02
## 2118 + + 2.263e-05
## 29 + 3.871e-05 -4.426e-03 -1.779e-02
## 2578 + + 1.974e-02
## 2570 + + -5.784e-03
## 526 + + 5.888e-06 -5.602e-03
## 534 + + 3.742e-05 1.867e-02
## 2634 + + -8.269e-03
## 2637 + -6.783e-05 -4.277e-03
## 590 + + -3.595e-05 -7.604e-03
## 2653 + -1.017e-04 7.253e-04 4.612e-02
## 30 + + 1.831e-05 -4.975e-03 3.991e-03
## 2074 + + -4.979e-03 4.245e-03
## 2141 + -8.321e-05 -1.126e-03 1.951e-02
## 2062 + + 1.653e-05 -5.498e-03
## 2566 + + 2.833e-05
## 2126 + + -1.192e-06 -8.083e-03
## 2573 + -3.481e-05 -1.705e-03
## 2585 + -1.319e-03 -2.677e-04
## 2581 + -2.643e-05 2.933e-03
## 2070 + + 2.540e-05 1.106e-02
## 2654 + + -4.060e-05 -2.329e-03 6.612e-02
## 2142 + + -1.919e-05 -4.387e-03 3.888e-02
## 2077 + -3.369e-05 -2.409e-03 -8.499e-03
## 541 + 3.923e-05 -3.795e-03 -9.782e-03
## 2630 + + 1.990e-05
## 2586 + + -3.939e-03 1.347e-02
## 542 + + 1.499e-05 -4.044e-03 1.296e-02
## 2582 + + 1.668e-05 1.953e-02
## 2574 + + 1.292e-05 -5.719e-03
## 2638 + + -4.741e-06 -8.297e-03
## 2078 + + 1.590e-05 -4.908e-03 4.191e-03
## 2589 + -3.479e-05 -1.717e-03 -8.192e-05
## 2590 + + 9.827e-06 -3.898e-03 1.341e-02
## ptn_arg_typ_cln prc_phs prs_typ stm_act stm_mdl tst_mss_or_dst tst_mth df
## 4028 + + + + + + 17
## 4026 + + + + + + 16
## 4090 + + + + + + + 17
## 1980 + + + + + 16
## 4092 + + + + + + + 18
## 4032 + + + + + + 18
## 2044 + + + + + + 17
## 2042 + + + + + + 16
## 4018 + + + + + + 15
## 4082 + + + + + + + 16
## 4030 + + + + + + 17
## 4020 + + + + + + 16
## 1984 + + + + + 17
## 2034 + + + + + + 15
## 1972 + + + + + 15
## 4094 + + + + + + + 18
## 1978 + + + + + 15
## 1982 + + + + + 16
## 1970 + + + + + 14
## 4096 + + + + + + + 19
## 2046 + + + + + + 17
## 2036 + + + + + + 16
## 4074 + + + + + + + 16
## 4084 + + + + + + + 17
## 2048 + + + + + + 18
## 4022 + + + + + + 16
## 1974 + + + + + 15
## 2038 + + + + + + 16
## 4086 + + + + + + + 17
## 4024 + + + + + + 17
## 1976 + + + + + 16
## 4066 + + + + + + + 15
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## logLik AICc delta weight
## 4028 -292.796 626.6 0.00 0.166
## 4026 -294.767 627.7 1.09 0.096
## 4090 -293.488 628.0 1.38 0.083
## 1980 -294.968 628.1 1.49 0.079
## 4092 -292.379 628.7 2.08 0.059
## 4032 -292.748 629.4 2.82 0.041
## 2044 -294.288 629.6 2.98 0.037
## 2042 -295.750 629.7 3.06 0.036
## 4018 -297.159 629.7 3.08 0.036
## 4082 -296.048 630.3 3.65 0.027
## 4030 -294.657 630.3 3.72 0.026
## 4020 -296.155 630.5 3.86 0.024
## 1984 -294.740 630.5 3.89 0.024
## 2034 -297.580 630.6 3.93 0.023
## 1972 -297.651 630.7 4.07 0.022
## 4094 -293.487 630.9 4.30 0.019
## 1978 -297.780 631.0 4.33 0.019
## 1982 -296.517 631.2 4.59 0.017
## 1970 -299.313 631.3 4.66 0.016
## 4096 -292.280 631.5 4.87 0.015
## 2046 -295.245 631.5 4.90 0.014
## 2036 -296.897 632.0 5.35 0.011
## 4074 -296.901 632.0 5.36 0.011
## 4084 -295.625 632.3 5.66 0.010
## 2048 -294.177 632.3 5.68 0.010
## 4022 -297.134 632.5 5.82 0.009
## 1974 -298.558 632.5 5.88 0.009
## 2038 -297.362 632.9 6.28 0.007
## 4086 -296.031 633.1 6.47 0.007
## 4024 -296.088 633.2 6.58 0.006
## 1976 -297.538 633.3 6.63 0.006
## 4066 -299.482 634.4 7.73 0.003
## 4076 -296.803 634.6 8.01 0.003
## 2040 -296.863 634.8 8.13 0.003
## 4078 -296.901 634.8 8.21 0.003
## 4088 -295.492 634.9 8.31 0.003
## 2026 -299.861 635.1 8.49 0.002
## 3896 -300.149 635.7 9.06 0.002
## 2018 -301.600 635.9 9.24 0.002
## 3960 -299.213 636.6 9.98 0.001
## 2030 -299.264 636.7 10.08 0.001
## 3904 -299.275 636.7 10.10 0.001
## 4070 -299.452 637.1 10.46 0.001
## 4068 -299.479 637.1 10.51 0.001
## 3892 -302.380 637.4 10.80 0.001
## 4080 -296.792 637.5 10.91 0.001
## 2028 -299.687 637.6 10.93 0.001
## 3968 -298.282 637.6 10.97 0.001
## 2022 -301.315 638.0 11.40 0.001
## 3900 -301.429 638.3 11.62 0.000
## 2020 -301.590 638.6 11.95 0.000
## 3958 -301.778 638.9 12.32 0.000
## 3956 -301.813 639.0 12.39 0.000
## 2032 -299.224 639.5 12.86 0.000
## 1844 -304.852 639.7 13.08 0.000
## 3964 -300.810 639.8 13.18 0.000
## 4072 -299.452 639.9 13.31 0.000
## 1908 -303.769 640.2 13.58 0.000
## 3942 -303.816 640.3 13.67 0.000
## 3954 -303.823 640.3 13.69 0.000
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## 4010 -302.744 640.9 14.25 0.000
## 3966 -301.356 640.9 14.27 0.000
## 956 -302.906 641.2 14.58 0.000
## 3944 -303.019 641.4 14.80 0.000
## 3938 -305.734 641.5 14.84 0.000
## 1020 -301.717 641.6 14.99 0.000
## 3890 -305.828 641.7 15.03 0.000
## 1912 -303.147 641.7 15.06 0.000
## 1848 -304.547 641.8 15.13 0.000
## 3946 -304.554 641.8 15.15 0.000
## 3894 -304.564 641.8 15.17 0.000
## 3962 -303.313 642.0 15.39 0.000
## 3948 -303.334 642.1 15.43 0.000
## 1852 -304.758 642.2 15.56 0.000
## 4012 -302.027 642.2 15.61 0.000
## 1018 -303.443 642.3 15.65 0.000
## 4002 -304.924 642.5 15.89 0.000
## 1916 -303.597 642.6 15.96 0.000
## 4014 -302.250 642.7 16.05 0.000
## 1906 -306.381 642.8 16.13 0.000
## 3940 -305.168 643.0 16.37 0.000
## 1890 -307.912 643.2 16.59 0.000
## 960 -302.572 643.3 16.70 0.000
## 1024 -301.184 643.4 16.78 0.000
## 3898 -305.529 643.7 17.10 0.000
## 1892 -306.959 643.9 17.29 0.000
## 3004 -302.899 644.0 17.35 0.000
## 3902 -304.342 644.1 17.45 0.000
## 1920 -303.073 644.3 17.70 0.000
## 1856 -304.508 644.4 17.78 0.000
## 3068 -301.695 644.4 17.80 0.000
## 4006 -304.642 644.7 18.05 0.000
## 4016 -301.836 644.7 18.08 0.000
## 4004 -304.683 644.8 18.13 0.000
## 1022 -303.344 644.9 18.24 0.000
## 1910 -306.124 644.9 18.29 0.000
## 3066 -303.440 645.1 18.43 0.000
## 1894 -307.635 645.3 18.64 0.000
## 1900 -306.370 645.4 18.78 0.000
## 1914 -306.379 645.4 18.80 0.000
## 1898 -307.739 645.5 18.85 0.000
## 1896 -306.481 645.6 19.00 0.000
## 954 -306.587 645.8 19.21 0.000
## 3008 -302.493 646.0 19.39 0.000
## 3072 -301.095 646.1 19.52 0.000
## 1966 -305.433 646.3 19.63 0.000
## 1958 -307.251 647.2 20.54 0.000
## 4008 -304.539 647.3 20.63 0.000
## 1842 -310.028 647.4 20.82 0.000
## 1904 -306.048 647.5 20.86 0.000
## 1918 -306.119 647.6 21.00 0.000
## 3070 -303.324 647.7 21.05 0.000
## 1902 -307.538 647.7 21.12 0.000
## 1724 -306.179 647.8 21.12 0.000
## 3884 -307.762 648.2 21.56 0.000
## 958 -306.561 648.5 21.89 0.000
## 1968 -305.168 648.5 21.89 0.000
## 3002 -306.570 648.5 21.91 0.000
## 1728 -305.427 649.0 22.41 0.000
## 3888 -306.850 649.1 22.47 0.000
## 1002 -308.398 649.5 22.84 0.000
## 1960 -307.191 649.8 23.15 0.000
## 1850 -309.895 649.8 23.16 0.000
## 1954 -309.921 649.8 23.22 0.000
## 3772 -305.889 650.0 23.33 0.000
## 1010 -308.673 650.0 23.39 0.000
## 1846 -310.021 650.0 23.41 0.000
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## 3876 -310.287 650.6 23.95 0.000
## 1964 -307.608 650.6 23.98 0.000
## 3882 -310.427 650.9 24.23 0.000
## 1956 -309.172 651.0 24.38 0.000
## 1014 -307.821 651.0 24.41 0.000
## 3874 -311.860 651.1 24.48 0.000
## 3006 -306.558 651.3 24.67 0.000
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## 3058 -308.120 651.6 25.01 0.000
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## 3776 -305.385 651.8 25.18 0.000
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## 3878 -311.317 652.6 26.01 0.000
## 3836 -305.850 652.7 26.11 0.000
## 1772 -308.679 652.8 26.12 0.000
## 1712 -308.682 652.8 26.13 0.000
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## 2996 -309.099 653.6 26.96 0.000
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## 2074 -375.431 766.0 139.39 0.000
## 2141 -376.583 766.0 139.40 0.000
## 2062 -375.442 766.0 139.41 0.000
## 2566 -375.521 766.2 139.57 0.000
## 2126 -374.375 766.2 139.62 0.000
## 2573 -377.861 766.3 139.70 0.000
## 2585 -377.890 766.4 139.76 0.000
## 2581 -377.891 766.4 139.76 0.000
## 2070 -375.646 766.4 139.82 0.000
## 2654 -372.161 766.7 140.04 0.000
## 2142 -373.492 766.9 140.25 0.000
## 2077 -378.175 767.0 140.33 0.000
## 541 -378.200 767.0 140.38 0.000
## 2630 -374.816 767.1 140.51 0.000
## 2586 -375.013 767.5 140.90 0.000
## 542 -375.014 767.5 140.90 0.000
## 2582 -375.147 767.8 141.17 0.000
## 2574 -375.150 767.8 141.17 0.000
## 2638 -374.087 768.1 141.44 0.000
## 2078 -375.426 768.4 141.72 0.000
## 2589 -377.861 768.6 141.95 0.000
## 2590 -375.011 769.9 143.29 0.000
## Models ranked by AICc(x)top <- weightable(res_test_method)
top <- top[top$aicc <= min(top$aicc) + 2,]
top## model
## 1 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 2 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 3 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 4 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 5 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 6 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + n_repetitions_sentence
## 7 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 8 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence
## 9 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 10 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 11 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 12 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed
## 13 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 14 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + character_identification
## 15 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 16 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence
## 17 d_calc ~ 1 + mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 18 d_calc ~ 1 + mean_age + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence
## 19 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## 20 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + presentation_type + test_mass_or_distributed + character_identification
## aicc weights
## 1 660.8949 0.06562237
## 2 660.8949 0.06562237
## 3 661.5400 0.04752994
## 4 661.5400 0.04752994
## 5 661.7956 0.04182609
## 6 661.7956 0.04182609
## 7 662.0483 0.03686245
## 8 662.0483 0.03686245
## 9 662.0817 0.03625228
## 10 662.0817 0.03625228
## 11 662.3370 0.03190830
## 12 662.3370 0.03190830
## 13 662.3376 0.03189774
## 14 662.3376 0.03189774
## 15 662.5565 0.02859067
## 16 662.5565 0.02859067
## 17 662.6773 0.02691577
## 18 662.6773 0.02691577
## 19 662.8049 0.02525145
## 20 662.8049 0.02525145summary(res_test_method@objects[[1]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -314.1141 652.4440 656.2282 693.3836 660.8949
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
##
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.4006 0.1987 -2.0164 0.0438
## agent_argument_type_cleannoun_phrase 0.1634 0.1458 1.1203 0.2626
## agent_argument_type_cleanpronoun -0.9581 0.1605 -5.9689 <.0001
## agent_argument_type_cleanvarying_agent 0.2469 0.1580 1.5625 0.1182
## patient_argument_type_cleannoun -0.0846 0.1016 -0.8323 0.4053
## patient_argument_type_cleannoun_phrase 0.9542 0.1402 6.8057 <.0001
## patient_argument_type_cleanpronoun 1.1007 0.1458 7.5518 <.0001
## patient_argument_type_cleanvarying_patient -0.4510 0.1667 -2.7055 0.0068
## presentation_typeimmediate_after 0.6529 0.1696 3.8486 0.0001
## presentation_typesimultaneous 0.4518 0.1678 2.6928 0.0071
## test_mass_or_distributedmass 0.3585 0.1009 3.5538 0.0004
## practice_phaseyes 0.1489 0.0762 1.9545 0.0506
## character_identificationyes 0.2226 0.0903 2.4638 0.0137
## n_repetitions_sentence 0.0190 0.0094 2.0272 0.0426
## ci.lb ci.ub
## intrcpt -0.7900 -0.0112 *
## agent_argument_type_cleannoun_phrase -0.1224 0.4491
## agent_argument_type_cleanpronoun -1.2727 -0.6435 ***
## agent_argument_type_cleanvarying_agent -0.0628 0.5567
## patient_argument_type_cleannoun -0.2837 0.1146
## patient_argument_type_cleannoun_phrase 0.6794 1.2290 ***
## patient_argument_type_cleanpronoun 0.8151 1.3864 ***
## patient_argument_type_cleanvarying_patient -0.7778 -0.1243 **
## presentation_typeimmediate_after 0.3204 0.9854 ***
## presentation_typesimultaneous 0.1230 0.7807 **
## test_mass_or_distributedmass 0.1608 0.5562 ***
## practice_phaseyes -0.0004 0.2982 .
## character_identificationyes 0.0455 0.3996 *
## n_repetitions_sentence 0.0006 0.0373 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_test_method, type="s")
summary(res_test_method@objects[[2]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -314.1141 652.4440 656.2282 693.3836 660.8949
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 91) = 652.4440, p-val < .0001
##
## Test of Moderators (coefficients 2:14):
## QM(df = 13) = 131.4274, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.4006 0.1987 -2.0164 0.0438
## sentence_structuretransitive -0.4510 0.1667 -2.7055 0.0068
## agent_argument_type_cleannoun_phrase 0.1634 0.1458 1.1203 0.2626
## agent_argument_type_cleanpronoun -0.9581 0.1605 -5.9689 <.0001
## agent_argument_type_cleanvarying_agent 0.2469 0.1580 1.5625 0.1182
## patient_argument_type_cleannoun 0.3665 0.1592 2.3028 0.0213
## patient_argument_type_cleannoun_phrase 1.4053 0.2104 6.6800 <.0001
## patient_argument_type_cleanpronoun 1.5518 0.2273 6.8285 <.0001
## presentation_typeimmediate_after 0.6529 0.1696 3.8486 0.0001
## presentation_typesimultaneous 0.4518 0.1678 2.6928 0.0071
## test_mass_or_distributedmass 0.3585 0.1009 3.5538 0.0004
## practice_phaseyes 0.1489 0.0762 1.9545 0.0506
## character_identificationyes 0.2226 0.0903 2.4638 0.0137
## n_repetitions_sentence 0.0190 0.0094 2.0272 0.0426
## ci.lb ci.ub
## intrcpt -0.7900 -0.0112 *
## sentence_structuretransitive -0.7778 -0.1243 **
## agent_argument_type_cleannoun_phrase -0.1224 0.4491
## agent_argument_type_cleanpronoun -1.2727 -0.6435 ***
## agent_argument_type_cleanvarying_agent -0.0628 0.5567
## patient_argument_type_cleannoun 0.0546 0.6784 *
## patient_argument_type_cleannoun_phrase 0.9929 1.8176 ***
## patient_argument_type_cleanpronoun 1.1064 1.9972 ***
## presentation_typeimmediate_after 0.3204 0.9854 ***
## presentation_typesimultaneous 0.1230 0.7807 **
## test_mass_or_distributedmass 0.1608 0.5562 ***
## practice_phaseyes -0.0004 0.2982 .
## character_identificationyes 0.0455 0.3996 *
## n_repetitions_sentence 0.0006 0.0373 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_test_method, type="s")
eval(metafor:::.glmulti)
coef(res_test_method)## Estimate Uncond. variance
## n_repetitions_video -0.0012128767 7.412201e-06
## test_methodpoint 0.0104179101 5.892855e-04
## stimuli_actorperson -0.0178686406 1.276884e-03
## mean_age 0.0001372364 3.601193e-08
## patient_argument_type_cleanvarying_patient -0.2034557802 5.441230e-02
## sentence_structuretransitive -0.2034557802 5.441230e-02
## practice_phaseyes 0.0737132825 8.448253e-03
## n_repetitions_sentence 0.0127128160 1.324853e-04
## character_identificationyes 0.1482561143 1.409528e-02
## intrcpt -0.3468533752 7.810498e-02
## agent_argument_type_cleannoun_phrase 0.1951506287 2.170645e-02
## agent_argument_type_cleanpronoun -0.9894954278 3.162697e-02
## agent_argument_type_cleanvarying_agent 0.1875619558 2.643901e-02
## patient_argument_type_cleannoun 0.1171260277 5.900592e-02
## patient_argument_type_cleannoun_phrase 1.1380758966 7.412955e-02
## patient_argument_type_cleanpronoun 1.3040830413 7.722776e-02
## presentation_typeimmediate_after 0.6017983845 3.621442e-02
## presentation_typesimultaneous 0.3409757341 3.432543e-02
## test_mass_or_distributedmass 0.4237189678 1.275075e-02
## Nb models Importance
## n_repetitions_video 2 0.03879071
## test_methodpoint 4 0.08632097
## stimuli_actorperson 6 0.14055753
## mean_age 12 0.41506278
## patient_argument_type_cleanvarying_patient 16 0.50000000
## sentence_structuretransitive 16 0.50000000
## practice_phaseyes 16 0.50133921
## n_repetitions_sentence 20 0.69231080
## character_identificationyes 24 0.75323808
## intrcpt 32 1.00000000
## agent_argument_type_cleannoun_phrase 32 1.00000000
## agent_argument_type_cleanpronoun 32 1.00000000
## agent_argument_type_cleanvarying_agent 32 1.00000000
## patient_argument_type_cleannoun 32 1.00000000
## patient_argument_type_cleannoun_phrase 32 1.00000000
## patient_argument_type_cleanpronoun 32 1.00000000
## presentation_typeimmediate_after 32 1.00000000
## presentation_typesimultaneous 32 1.00000000
## test_mass_or_distributedmass 32 1.00000000
## +/- (alpha=0.05)
## n_repetitions_video 0.0053360721
## test_methodpoint 0.0475785235
## stimuli_actorperson 0.0700364072
## mean_age 0.0003719386
## patient_argument_type_cleanvarying_patient 0.4571899107
## sentence_structuretransitive 0.4571899107
## practice_phaseyes 0.1801488691
## n_repetitions_sentence 0.0225596306
## character_identificationyes 0.2326939045
## intrcpt 0.5477563949
## agent_argument_type_cleannoun_phrase 0.2887636105
## agent_argument_type_cleanpronoun 0.3485594822
## agent_argument_type_cleanvarying_agent 0.3186916488
## patient_argument_type_cleannoun 0.4760974652
## patient_argument_type_cleannoun_phrase 0.5336343553
## patient_argument_type_cleanpronoun 0.5446716902
## presentation_typeimmediate_after 0.3729828336
## presentation_typesimultaneous 0.3631249418
## test_mass_or_distributedmass 0.2213176272mmi <- as.data.frame(coef(res_test_method))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)## Estimate Std. Error z value Pr(>|z|)
## intrcpt -0.3469 0.2795 -1.2411 0.2146
## agent_argument_type_cleannoun_phrase 0.1952 0.1473 1.3246 0.1853
## agent_argument_type_cleanpronoun -0.9895 0.1778 -5.5640 0.0000
## agent_argument_type_cleanvarying_agent 0.1876 0.1626 1.1535 0.2487
## patient_argument_type_cleannoun 0.1171 0.2429 0.4822 0.6297
## patient_argument_type_cleannoun_phrase 1.1381 0.2723 4.1800 0.0000
## patient_argument_type_cleanpronoun 1.3041 0.2779 4.6927 0.0000
## presentation_typeimmediate_after 0.6018 0.1903 3.1624 0.0016
## presentation_typesimultaneous 0.3410 0.1853 1.8404 0.0657
## test_mass_or_distributedmass 0.4237 0.1129 3.7524 0.0002
## character_identificationyes 0.1483 0.1187 1.2488 0.2118
## n_repetitions_sentence 0.0127 0.0115 1.1045 0.2694
## practice_phaseyes 0.0737 0.0919 0.8020 0.4226
## sentence_structuretransitive -0.2035 0.2333 -0.8722 0.3831
## patient_argument_type_cleanvarying_patient -0.2035 0.2333 -0.8722 0.3831
## mean_age 0.0001 0.0002 0.7232 0.4696
## stimuli_actorperson -0.0179 0.0357 -0.5001 0.6170
## test_methodpoint 0.0104 0.0243 0.4292 0.6678
## n_repetitions_video -0.0012 0.0027 -0.4455 0.6560
## ci.lb ci.ub Importance
## intrcpt -0.8946 0.2009 1.0000
## agent_argument_type_cleannoun_phrase -0.0936 0.4839 1.0000
## agent_argument_type_cleanpronoun -1.3381 -0.6409 1.0000
## agent_argument_type_cleanvarying_agent -0.1311 0.5063 1.0000
## patient_argument_type_cleannoun -0.3590 0.5932 1.0000
## patient_argument_type_cleannoun_phrase 0.6044 1.6717 1.0000
## patient_argument_type_cleanpronoun 0.7594 1.8488 1.0000
## presentation_typeimmediate_after 0.2288 0.9748 1.0000
## presentation_typesimultaneous -0.0221 0.7041 1.0000
## test_mass_or_distributedmass 0.2024 0.6450 1.0000
## character_identificationyes -0.0844 0.3810 0.7532
## n_repetitions_sentence -0.0098 0.0353 0.6923
## practice_phaseyes -0.1064 0.2539 0.5013
## sentence_structuretransitive -0.6606 0.2537 0.5000
## patient_argument_type_cleanvarying_patient -0.6606 0.2537 0.5000
## mean_age -0.0002 0.0005 0.4151
## stimuli_actorperson -0.0879 0.0522 0.1406
## test_methodpoint -0.0372 0.0580 0.0863
## n_repetitions_video -0.0065 0.0041 0.0388take stimuli modality
res_stimuli_modality <- glmulti(d_calc ~mean_age + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video, data=ma_data, level=1, fitfunction=rma.glmulti, crit="aicc", confsetsize=32)## Initialization...
## TASK: Exhaustive screening of candidate set.
## Fitting...
##
## After 50 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor
## Crit= 703.139154580491
## Mean crit= 726.927294368649
##
## After 100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+presentation_type
## Crit= 685.621375640315
## Mean crit= 704.902195771666
##
## After 150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type
## Crit= 679.326562070076
## Mean crit= 691.69364491043
##
## After 200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed
## Crit= 658.04629132771
## Mean crit= 680.112874528386
##
## After 250 models:
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 654.840389646851
## Mean crit= 671.055451082595
##
## After 300 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 666.406910711395
##
## After 350 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 664.826888009878
##
## After 400 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 662.026036119666
##
## After 450 models:
## Best model: d_calc~1+mean_age+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Best model: d_calc~1+mean_age+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed
## Crit= 647.169614006741
## Mean crit= 661.80561850372
##
## After 500 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+test_mass_or_distributed+practice_phase
## Crit= 643.215901075392
## Mean crit= 657.116876940897
##
## After 550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464##
## After 600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464
##
## After 650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464##
## After 700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.849105935464##
## After 750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 652.039344274024
##
## After 800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042##
## After 850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042
##
## After 900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042##
## After 950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 650.614824656042##
## After 1000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 649.027793085993
##
## After 1050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 648.906804481044
##
## After 1100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355##
## After 1150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355
##
## After 1200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355##
## After 1250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355##
## After 1300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 646.862262553355##
## After 1350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.86694151453##
## After 1400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.86694151453
##
## After 1450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.86694151453##
## After 1500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 645.460382494939
##
## After 1550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase
## Crit= 635.866689784983
## Mean crit= 644.8481747198
##
## After 1600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361##
## After 1650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361
##
## After 1700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361##
## After 1750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361##
## After 1800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361##
## After 1850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 643.063146365361##
## After 1900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.984538021898##
## After 1950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.984538021898
##
## After 2000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.984538021898##
## After 2050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.796141432037
##
## After 2100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 642.666761153361
##
## After 2150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268##
## After 2200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268
##
## After 2250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268##
## After 2300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268##
## After 2350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence
## Crit= 635.115943076111
## Mean crit= 641.529629381268##
## After 2400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692##
## After 2450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692
##
## After 2500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692##
## After 2550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.677845295692##
## After 2600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+n_repetitions_video
## Crit= 631.29215097818
## Mean crit= 639.463467797289
##
## After 2650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282##
## After 2700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282
##
## After 2750 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282##
## After 2800 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.762404166282##
## After 2850 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.301836506431##
## After 2900 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 637.301836506431
##
## After 2950 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875##
## After 3000 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875
##
## After 3050 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875##
## After 3100 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.925287143875##
## After 3150 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 635.828104104437
##
## After 3200 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214##
## After 3250 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214
##
## After 3300 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214##
## After 3350 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214##
## After 3400 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 634.936246303214##
## After 3450 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584##
## After 3500 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584
##
## After 3550 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584##
## After 3600 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584##
## After 3650 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584##
## After 3700 models:
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_video
## Crit= 630.553150292753
## Mean crit= 633.872678115584##
## After 3750 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289##
## After 3800 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289
##
## After 3850 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289##
## After 3900 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289##
## After 3950 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Best model: d_calc~1+sentence_structure+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+practice_phase+n_repetitions_sentence+n_repetitions_video
## Crit= 629.682535581113
## Mean crit= 632.910833251289##
## After 4000 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817##
## After 4050 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817
##
## After 4100 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817##
## After 4150 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817##
## After 4200 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.933838040817##
## After 4250 models:
## Best model: d_calc~1+agent_argument_type_clean+patient_argument_type_clean+stimuli_actor+stimuli_modality+presentation_type+test_mass_or_distributed+character_identification+n_repetitions_sentence+n_repetitions_video
## Crit= 628.117824759403
## Mean crit= 631.367357490081
## Completed.print(res)## Global model call: rma.mv(yi = d_calc, V = d_var_calc, mods = ~mean_age + agent_argument_type_clean +
## patient_argument_type_clean + stimuli_modality + stimuli_actor +
## presentation_type + test_mass_or_distributed + practice_phase +
## character_identification + n_repetitions_sentence + n_repetitions_video +
## test_method, data = ma_data, method = "ML")
## ---
## Model selection table
## (Int) agn_arg_typ_cln chr_idn men_age n_rpt_snt n_rpt_vid
## 4028 + + + 2.482e-02 -1.557e-01
## 4026 + + 2.037e-02 -1.422e-01
## 4090 + + 2.110e-02 -1.083e-01
## 1980 + + + 2.196e-02 -1.757e-01
## 4092 + + + 2.443e-02 -1.322e-01
## 4032 + + + -6.528e-05 2.476e-02 -1.582e-01
## 2044 + + + 2.166e-02 -1.446e-01
## 2042 + + 1.755e-02 -1.181e-01
## 4018 + + -1.402e-01
## 4082 + + -1.086e-01
## 4030 + + 9.070e-05 2.086e-02 -1.399e-01
## 4020 + + + -1.493e-01
## 1984 + + + 1.257e-04 2.250e-02 -1.680e-01
## 2034 + + -1.167e-01
## 1972 + + + -1.667e-01
## 4094 + + 9.039e-06 2.114e-02 -1.083e-01
## 1978 + + 1.600e-02 -1.632e-01
## 1982 + + 2.699e-04 1.881e-02 -1.500e-01
## 1970 + + -1.587e-01
## 4096 + + + -9.424e-05 2.431e-02 -1.341e-01
## 2046 + + 1.798e-04 1.916e-02 -1.168e-01
## 2036 + + + -1.340e-01
## 4074 + + 2.118e-02
## 4084 + + + -1.230e-01
## 2048 + + + 8.919e-05 2.207e-02 -1.414e-01
## 4022 + + 4.295e-05 -1.391e-01
## 1974 + + 2.049e-04 -1.481e-01
## 2038 + + 1.164e-04 -1.158e-01
## 4086 + + -3.697e-05 -1.084e-01
## 4024 + + + -7.645e-05 -1.522e-01
## 1976 + + + 8.849e-05 -1.611e-01
## 4066 + +
## 4076 + + + 2.211e-02
## 2040 + + + 4.932e-05 -1.322e-01
## 4078 + + -2.502e-06 2.117e-02
## 4088 + + + -1.089e-04 -1.253e-01
## 2026 + + 1.710e-02
## 3896 + + + -3.662e-04 -1.411e-01
## 2018 + +
## 3960 + + + -3.991e-04 -1.100e-01
## 2030 + + 1.956e-04 1.886e-02
## 3904 + + + -3.599e-04 1.036e-02 -1.309e-01
## 4070 + + -4.858e-05
## 4068 + + +
## 3892 + + + -1.278e-01
## 4080 + + + -3.214e-05 2.206e-02
## 2028 + + + 1.840e-02
## 3968 + + + -3.936e-04 1.070e-02 -9.859e-02
## 2022 + + 1.330e-04
## 3900 + + + 1.081e-02 -1.175e-01
## 2020 + + +
## 3958 + + -3.513e-04 -7.368e-02
## 3956 + + + -1.029e-01
## 2032 + + + 1.801e-04 1.937e-02
## 1844 + + + -1.350e-01
## 3964 + + + 1.110e-02 -9.120e-02
## 4072 + + + -4.922e-05
## 1908 + + + -1.003e-01
## 3942 + + -3.401e-04
## 3954 + + -7.132e-02
## 3952 + + + -3.594e-04 1.459e-02
## 2024 + + + 1.396e-04
## 3950 + + -3.314e-04 1.083e-02
## 4010 + + 1.944e-02
## 3966 + + -3.440e-04 7.079e-03 -6.339e-02
## 956 + + + 3.340e-02 -1.998e-01
## 3944 + + + -3.616e-04
## 3938 + +
## 1020 + + + 3.258e-02 -1.579e-01
## 3890 + + -1.088e-01
## 1912 + + + -1.734e-04 -1.027e-01
## 1848 + + + -1.186e-04 -1.405e-01
## 3946 + + 1.131e-02
## 3894 + + -2.707e-04 -1.164e-01
## 3962 + + 7.772e-03 -6.007e-02
## 3948 + + + 1.470e-02
## 1852 + + + 3.135e-03 -1.325e-01
## 4012 + + + 2.202e-02
## 1018 + + 2.831e-02 -1.293e-01
## 4002 + +
## 1916 + + + 4.282e-03 -9.552e-02
## 4014 + + 1.907e-04 2.049e-02
## 1906 + + -6.356e-02
## 3940 + + +
## 1890 + +
## 960 + + + -1.418e-04 3.194e-02 -2.067e-01
## 1024 + + + -1.809e-04 3.064e-02 -1.629e-01
## 3898 + + 5.905e-03 -1.019e-01
## 1892 + + +
## 3004 + + + 3.310e-02 -2.004e-01
## 3902 + + -2.631e-04 5.115e-03 -1.103e-01
## 1920 + + + -1.619e-04 2.850e-03 -9.935e-02
## 1856 + + + -1.098e-04 2.061e-03 -1.384e-01
## 3068 + + + 3.203e-02 -1.587e-01
## 4006 + + 1.432e-04
## 4016 + + + 1.263e-04 2.223e-02
## 4004 + + +
## 1022 + + -7.428e-05 2.721e-02 -1.294e-01
## 1910 + + -1.098e-04 -6.314e-02
## 3066 + + 2.811e-02 -1.295e-01
## 1894 + + -1.141e-04
## 1900 + + + 7.749e-03
## 1914 + + 4.205e-04 -6.287e-02
## 1898 + + 3.983e-03
## 1896 + + + -1.518e-04
## 954 + + 2.721e-02 -1.868e-01
## 3008 + + + -1.871e-04 3.271e-02 -2.063e-01
## 3072 + + + -2.290e-04 3.145e-02 -1.624e-01
## 1966 + + 4.372e-04 1.775e-02
## 1958 + + 3.737e-04
## 4008 + + + 1.097e-04
## 1842 + + -1.134e-01
## 1904 + + + -1.263e-04 6.740e-03
## 1918 + + -1.133e-04 -7.283e-04 -6.431e-02
## 3070 + + -9.630e-05 2.757e-02 -1.288e-01
## 1902 + + -9.941e-05 3.047e-03
## 1724 + + + 2.436e-02 -9.189e-02
## 3884 + + + 1.715e-02
## 958 + + 3.672e-05 2.778e-02 -1.854e-01
## 1968 + + + 3.909e-04 1.908e-02
## 3002 + + 2.773e-02 -1.859e-01
## 1728 + + + 2.269e-04 2.526e-02 -8.047e-02
## 3888 + + + -2.298e-04 1.733e-02
## 1002 + + 2.842e-02
## 1960 + + + 3.499e-04
## 1850 + + -3.580e-03 -1.172e-01
## 1954 + +
## 3772 + + + 2.547e-02 -8.128e-02
## 1010 + + -1.299e-01
## 1846 + + 1.805e-05 -1.128e-01
## 1788 + + + 2.437e-02 -9.598e-02
## 1962 + + 1.278e-02
## 3876 + + +
## 1964 + + + 1.667e-02
## 3882 + + 1.245e-02
## 1956 + + +
## 1014 + + -2.104e-04 -1.300e-01
## 3874 + +
## 3006 + + 2.942e-05 2.790e-02 -1.852e-01
## 3880 + + + -2.232e-04
## 1016 + + + -2.989e-04 -1.541e-01
## 3058 + + -1.324e-01
## 1716 + + + -7.945e-02
## 1004 + + + 2.980e-02
## 1792 + + + 2.352e-04 2.533e-02 -8.967e-02
## 1012 + + + -1.444e-01
## 3776 + + + 2.032e-04 2.563e-02 -7.728e-02
## 1006 + + -7.191e-05 2.736e-02
## 948 + + + -1.918e-01
## 3050 + + 2.879e-02
## 1854 + + -2.290e-06 -3.609e-03 -1.173e-01
## 3886 + + -1.693e-04 1.229e-02
## 952 + + + -2.588e-04 -2.051e-01
## 3878 + + -1.755e-04
## 3836 + + + 2.558e-02 -8.925e-02
## 1772 + + + 2.180e-02
## 1712 + + + 3.662e-04 2.212e-02
## 946 + + -1.837e-01
## 3060 + + + -1.500e-01
## 1710 + + 4.796e-04 1.943e-02
## 3756 + + + 2.359e-02
## 1726 + + 4.400e-04 2.028e-02 -4.725e-02
## 1776 + + + 2.803e-04 2.315e-02
## 1720 + + + 1.886e-04 -6.957e-02
## 2996 + + + -1.984e-01
## 3062 + + -1.688e-04 -1.311e-01
## 1774 + + 4.095e-04 2.019e-02
## 3820 + + + 2.387e-02
## 1008 + + + -1.091e-04 2.858e-02
## 3764 + + + -7.422e-02
## 3760 + + + 2.590e-04 2.391e-02
## 1708 + + + 1.973e-02
## 3064 + + + -2.678e-04 -1.546e-01
## 1780 + + + -8.260e-02
## 3052 + + + 3.007e-02
## 3840 + + + 2.086e-04 2.577e-02 -8.733e-02
## 3054 + + -1.185e-04 2.811e-02
## 1702 + + 4.116e-04
## 1828 + + +
## 2994 + + -1.876e-01
## 950 + + -9.900e-05 -1.877e-01
## 1718 + + 3.722e-04 -4.372e-02
## 3000 + + + -2.208e-04 -2.054e-01
## 3758 + + 4.257e-04 2.026e-02
## 1764 + + +
## 1704 + + + 3.153e-04
## 3824 + + + 2.260e-04 2.412e-02
## 1790 + + 4.217e-04 2.039e-02 -3.746e-02
## 3774 + + 4.357e-04 2.034e-02 -4.655e-02
## 1766 + + 3.457e-04
## 1784 + + + 1.952e-04 -7.693e-02
## 3768 + + + 1.942e-04 -7.035e-02
## 1700 + + +
## 1836 + + + 8.338e-03
## 1768 + + + 2.374e-04
## 3748 + + +
## 3822 + + 3.935e-04 2.046e-02
## 3056 + + + -1.701e-04 2.961e-02
## 1770 + + 1.642e-02
## 3828 + + + -7.908e-02
## 3750 + + 3.780e-04
## 994 + +
## 1762 + +
## 1722 + + 1.568e-02 -5.840e-02
## 1832 + + + 2.156e-05
## 3812 + + +
## 2998 + + -4.190e-05 -1.885e-01
## 1714 + + -5.420e-02
## 3752 + + + 2.459e-04
## 1782 + + 3.567e-04 -3.560e-02
## 3766 + + 3.877e-04 -4.616e-02
## 1826 + +
## 3754 + + 1.762e-02
## 998 + + -2.087e-04
## 3818 + + 1.811e-02
## 3838 + + 4.208e-04 2.041e-02 -3.734e-02
## 3814 + + 3.463e-04
## 1840 + + + 5.046e-05 8.725e-03
## 1698 + +
## 3770 + + 1.763e-02 -4.380e-02
## 3832 + + + 1.979e-04 -7.718e-02
## 1706 + + 1.408e-02
## 1786 + + 1.649e-02 -3.072e-02
## 3746 + +
## 3816 + + + 2.139e-04
## 3042 + +
## 1778 + + -3.003e-02
## 3810 + +
## 3762 + + -4.372e-02
## 888 + + + -4.606e-04 -1.080e-01
## 996 + + +
## 1830 + + 9.961e-05
## 700 + + + 3.557e-02 -1.165e-01
## 1834 + + 2.257e-03
## 3830 + + 3.740e-04 -3.784e-02
## 1260 + + + 1.897e-02
## 3834 + + 1.798e-02 -2.361e-02
## 1000 + + + -2.232e-04
## 3046 + + -1.929e-04
## 2936 + + + -5.650e-04 -1.111e-01
## 1200 + + + 3.137e-04 1.899e-02
## 2748 + + + 3.249e-02 -1.274e-01
## 1198 + + 4.243e-04 1.641e-02
## 3826 + + -2.541e-02
## 3044 + + +
## 896 + + + -4.328e-04 5.834e-03 -1.011e-01
## 1196 + + + 1.707e-02
## 1264 + + + 2.296e-04 1.999e-02
## 1190 + + 3.691e-04
## 1252 + + +
## 1838 + + 1.159e-04 3.456e-03
## 1516 + + + 1.776e-02
## 1262 + + 3.554e-04 1.714e-02
## 1188 + + +
## 2944 + + + -5.612e-04 9.540e-03 -1.009e-01
## 3244 + + + 1.943e-02
## 1192 + + + 2.726e-04
## 704 + + + -4.733e-05 3.510e-02 -1.183e-01
## 1506 + +
## 764 + + + 3.548e-02 -1.090e-01
## 3308 + + + 1.982e-02
## 1212 + + + 1.820e-02 -3.127e-02
## 1508 + + +
## 1254 + + 3.036e-04
## 1514 + + 1.333e-02
## 1518 + + 2.920e-04 1.607e-02
## 1276 + + + 1.892e-02 3.791e-03
## 3048 + + + -2.094e-04
## 1216 + + + 2.764e-04 1.944e-02 -1.871e-02
## 1510 + + 2.368e-04
## 1256 + + + 1.952e-04
## 3248 + + + 2.619e-04 1.976e-02
## 1250 + +
## 1454 + + 4.109e-04 1.579e-02
## 1572 + + +
## 1520 + + + 2.054e-04 1.887e-02
## 824 + + + -4.062e-04 -1.692e-01
## 1456 + + + 3.135e-04 1.878e-02
## 1446 + + 3.548e-04
## 1258 + + 1.402e-02
## 2812 + + + 3.222e-02 -1.159e-01
## 2752 + + + 7.295e-05 3.266e-02 -1.267e-01
## 3246 + + 4.131e-04 1.656e-02
## 1204 + + + -2.600e-02
## 1214 + + 4.236e-04 1.641e-02 -5.812e-04
## 3949 + -5.348e-04 1.644e-02
## 1522 + + 3.584e-02
## 1278 + + 3.534e-04 1.743e-02 3.121e-02
## 3236 + + +
## 872 + + + -4.429e-04
## 1452 + + + 1.684e-02
## 3620 + + +
## 1280 + + + 2.371e-04 1.990e-02 1.007e-02
## 3312 + + + 2.244e-04 2.007e-02
## 3951 + + -5.642e-04 2.006e-02
## 1588 + + + -3.344e-02
## 3564 + + + 1.867e-02
## 3238 + + 3.743e-04
## 1206 + + 3.689e-04 -1.688e-04
## 3300 + + +
## 1268 + + + 7.015e-03
## 1530 + + 1.367e-02 3.739e-02
## 886 + + -4.007e-04 -6.303e-02
## 1186 + +
## 1534 + + 2.850e-04 1.632e-02 3.550e-02
## 1532 + + + 1.749e-02 1.340e-02
## 1444 + + +
## 3260 + + + 1.954e-02 -1.923e-02
## 1270 + + 3.009e-04 2.922e-02
## 3310 + + 3.768e-04 1.685e-02
## 1512 + + + 1.658e-04
## 3967 + + -5.875e-04 1.753e-02 -5.808e-02
## 1208 + + + 2.427e-04 -1.466e-02
## 870 + + -4.050e-04
## 1448 + + + 2.734e-04
## 3500 + + + 1.891e-02
## 880 + + + -3.980e-04 9.807e-03
## 1526 + + 2.292e-04 3.409e-02
## 2872 + + + -5.196e-04 -1.717e-01
## 3554 + +
## 1636 + + +
## 3240 + + + 2.506e-04
## 768 + + + -5.191e-05 3.494e-02 -1.101e-01
## 1266 + + 3.024e-02
## 1524 + + + 1.858e-02
## 3302 + + 3.385e-04
## 1901 + -3.698e-04 1.187e-02
## 1194 + + 1.186e-02
## 3562 + + 1.417e-02
## 3556 + + +
## 1468 + + + 1.783e-02 -3.188e-02
## 1274 + + 1.433e-02 3.203e-02
## 3324 + + + 1.981e-02 9.682e-03
## 2928 + + + -5.270e-04 1.352e-02
## 1919 + + -4.353e-04 1.278e-02 -6.581e-02
## 1580 + + + 4.596e-03
## 3628 + + + 7.940e-03
## 2934 + + -5.146e-04 -6.694e-02
## 3965 + -5.416e-04 1.431e-02 -3.203e-02
## 3566 + + 2.966e-04 1.602e-02
## 832 + + + -3.820e-04 4.930e-03 -1.641e-01
## 1903 + + -3.942e-04 1.522e-02
## 3636 + + + -2.587e-02
## 1442 + +
## 1272 + + + 2.049e-04 1.258e-02
## 3264 + + + 2.510e-04 1.983e-02 -1.531e-02
## 3558 + + 2.531e-04
## 2920 + + + -5.276e-04
## 3304 + + + 2.143e-04
## 1472 + + + 2.750e-04 1.914e-02 -1.926e-02
## 1909 + -4.567e-04 -5.541e-02
## 3298 + +
## 1893 + -4.550e-04
## 3234 + +
## 1576 + + + -1.145e-05
## 3502 + + 3.787e-04 1.608e-02
## 3492 + + +
## 3504 + + + 2.537e-04 1.942e-02
## 3624 + + + -1.416e-04
## 3570 + + 4.199e-02
## 3903 + + -5.336e-04 1.629e-02 -1.033e-01
## 1536 + + + 2.155e-04 1.856e-02 1.786e-02
## 1470 + + 4.061e-04 1.578e-02 -3.881e-03
## 3306 + + 1.466e-02
## 1911 + + -5.118e-04 -7.998e-02
## 3252 + + + -1.812e-02
## 748 + + + 3.310e-02
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## 607 + + -1.570e-04 2.894e-03 -3.970e-02
## 1029 + 2.660e-04
## 3665 + 6.720e-02
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## 3074 + +
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## 2592 + + + -2.145e-04 3.086e-03 -2.970e-02
## 2773 + -5.818e-05 -8.558e-03
## 2655 + + -2.881e-04 6.601e-03 -2.738e-02
## 2563 + +
## 3157 + 8.168e-05 5.371e-02
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## 1109 + 2.360e-04 4.004e-02
## 3161 + -1.515e-03 5.285e-02
## 3154 + + 5.314e-02
## 3093 + 1.355e-04 3.093e-02
## 3077 + 1.434e-04
## 1037 + 2.145e-04 -6.623e-03
## 1097 + -1.068e-02
## 2652 + + + 3.381e-03 -5.498e-03
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## 1093 + 2.153e-04
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## 3601 + 3.366e-02
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## 527 + + -9.965e-07 6.832e-03
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## 1621 + 2.041e-04 5.344e-02
## 1106 + + 4.984e-02
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## 1541 + 2.689e-04
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## 1101 + 1.465e-04 -7.495e-03
## 3085 + 1.111e-04 -5.882e-03
## 3673 + -2.975e-04 6.651e-02
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## 3138 + +
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## 1117 + 1.935e-04 -4.304e-03 3.421e-02
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## 1089 +
## 1053 + 2.454e-04 -5.570e-03 8.703e-03
## 3086 + + 1.394e-04 -5.769e-03
## 3589 + 1.469e-04
## 1098 + + -1.012e-02
## 3101 + 1.258e-04 -1.910e-03 2.784e-02
## 3605 + 1.332e-04 3.239e-02
## 3162 + + -2.118e-03 4.985e-02
## 1549 + 2.161e-04 -6.614e-03
## 1622 + + 1.827e-04 6.400e-02
## 1090 + +
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## 1558 + + 2.547e-04 2.914e-02
## 3606 + + 1.429e-04 3.665e-02
## 1625 + -7.226e-03 4.272e-02
## 3146 + + -7.047e-03
## 3649 +
## 1557 + 2.994e-04 1.707e-02
## 1538 + +
## 1605 + 2.185e-04
## 3609 + -3.088e-03 2.810e-02
## 3590 + + 1.542e-04
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## 3149 + 8.904e-05 -6.737e-03
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## 1629 + 1.751e-04 -3.261e-03 4.769e-02
## 1118 + + 1.921e-04 -4.460e-03 4.064e-02
## 1626 + + -4.949e-03 6.078e-02
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## 3610 + + -1.735e-03 3.475e-02
## 3674 + + -7.638e-04 6.756e-02
## 3597 + 1.147e-04 -5.761e-03
## 1613 + 1.483e-04 -7.484e-03
## 3677 + 6.134e-05 2.147e-04 6.524e-02
## 1049 + -1.245e-02 -1.197e-02
## 1554 + + 2.659e-02
## 1545 + -1.163e-02
## 3650 + +
## 1601 +
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## 3653 + 1.351e-04
## 1606 + + 2.314e-04
## 1565 + 2.439e-04 -5.424e-03 1.024e-02
## 1610 + + -1.007e-02
## 3150 + + 1.336e-04 -6.211e-03
## 3613 + 1.245e-04 -1.775e-03 2.928e-02
## 1602 + +
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## 1562 + + -7.444e-03 1.652e-02
## 1025 +
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## 1614 + + 1.836e-04 -7.876e-03
## 3654 + + 1.542e-04
## 3661 + 9.248e-05 -6.617e-03
## 3678 + + 9.664e-05 -3.620e-04 6.524e-02
## 1561 + -1.211e-02 -8.960e-03
## 1537 +
## 65 +
## 1041 + -8.511e-03
## 3662 + + 1.326e-04 -6.242e-03
## 594 + + 6.909e-02
## 577 +
## 593 + 3.828e-02
## 2 + +
## 82 + + 4.508e-02
## 73 + -3.510e-03
## 81 + 1.535e-02
## 1553 + -1.344e-03
## 2113 +
## 69 + 2.255e-05
## 2049 +
## 66 + +
## 10 + + -5.666e-03
## 585 + -3.430e-03
## 1 +
## 514 + +
## 74 + + -7.072e-03
## 2625 +
## 513 +
## 2129 + 1.803e-02
## 598 + + -3.247e-05 7.023e-02
## 602 + + -1.595e-03 6.605e-02
## 2641 + 3.861e-02
## 2642 + + 6.917e-02
## 581 + 9.271e-06
## 2561 +
## 18 + + 9.858e-03
## 597 + -1.684e-05 3.914e-02
## 601 + -3.734e-04 3.742e-02
## 5 + 1.066e-04
## 90 + + -3.828e-03 3.939e-02
## 89 + -2.618e-03 1.122e-02
## 6 + + 4.442e-05
## 2050 + +
## 2121 + -2.641e-03
## 77 + -2.258e-05 -4.180e-03
## 85 + 1.807e-05 1.506e-02
## 2117 + -4.152e-05
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## 578 + +
## 17 + -1.738e-02
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## 2114 + +
## 517 + 8.490e-05
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## 586 + + -7.058e-03
## 589 + -4.214e-05 -4.675e-03
## 2645 + -1.047e-04 4.455e-02
## 21 + 8.758e-05 -1.273e-02
## 26 + + -5.275e-03 3.512e-03
## 14 + + 1.468e-05 -5.468e-03
## 2633 + -3.363e-03
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## 13 + 8.974e-05 -1.807e-03
## 2565 + -2.274e-05
## 22 + + 4.686e-05 1.016e-02
## 2577 + 2.221e-03
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## 2650 + + -2.188e-03 6.510e-02
## 2125 + -6.855e-05 -3.567e-03
## 2646 + + -3.711e-05 7.035e-02
## 605 + -2.955e-05 -1.299e-03 3.678e-02
## 93 + -1.371e-05 -3.063e-03 1.074e-02
## 2054 + + 3.121e-05
## 94 + + -2.525e-05 -4.218e-03 3.931e-02
## 2138 + + -4.307e-03 3.856e-02
## 582 + + 1.114e-05
## 2073 + -2.021e-03 -8.655e-03
## 2626 + +
## 2134 + + -1.110e-05 4.538e-02
## 2069 + -2.172e-05 -4.664e-03
## 2061 + -3.548e-05 -9.866e-04
## 537 + -5.222e-03 -1.268e-02
## 525 + 6.052e-05 -2.521e-03
## 533 + 8.053e-05 -4.761e-03
## 538 + + -4.286e-03 1.260e-02
## 2118 + + 2.263e-05
## 29 + 3.871e-05 -4.426e-03 -1.779e-02
## 2578 + + 1.974e-02
## 2570 + + -5.784e-03
## 526 + + 5.888e-06 -5.602e-03
## 534 + + 3.742e-05 1.867e-02
## 2634 + + -8.269e-03
## 2637 + -6.783e-05 -4.277e-03
## 590 + + -3.595e-05 -7.604e-03
## 2653 + -1.017e-04 7.253e-04 4.612e-02
## 30 + + 1.831e-05 -4.975e-03 3.991e-03
## 2074 + + -4.979e-03 4.245e-03
## 2141 + -8.321e-05 -1.126e-03 1.951e-02
## 2062 + + 1.653e-05 -5.498e-03
## 2566 + + 2.833e-05
## 2126 + + -1.192e-06 -8.083e-03
## 2573 + -3.481e-05 -1.705e-03
## 2585 + -1.319e-03 -2.677e-04
## 2581 + -2.643e-05 2.933e-03
## 2070 + + 2.540e-05 1.106e-02
## 2654 + + -4.060e-05 -2.329e-03 6.612e-02
## 2142 + + -1.919e-05 -4.387e-03 3.888e-02
## 2077 + -3.369e-05 -2.409e-03 -8.499e-03
## 541 + 3.923e-05 -3.795e-03 -9.782e-03
## 2630 + + 1.990e-05
## 2586 + + -3.939e-03 1.347e-02
## 542 + + 1.499e-05 -4.044e-03 1.296e-02
## 2582 + + 1.668e-05 1.953e-02
## 2574 + + 1.292e-05 -5.719e-03
## 2638 + + -4.741e-06 -8.297e-03
## 2078 + + 1.590e-05 -4.908e-03 4.191e-03
## 2589 + -3.479e-05 -1.717e-03 -8.192e-05
## 2590 + + 9.827e-06 -3.898e-03 1.341e-02
## ptn_arg_typ_cln prc_phs prs_typ stm_act stm_mdl tst_mss_or_dst tst_mth df
## 4028 + + + + + + 17
## 4026 + + + + + + 16
## 4090 + + + + + + + 17
## 1980 + + + + + 16
## 4092 + + + + + + + 18
## 4032 + + + + + + 18
## 2044 + + + + + + 17
## 2042 + + + + + + 16
## 4018 + + + + + + 15
## 4082 + + + + + + + 16
## 4030 + + + + + + 17
## 4020 + + + + + + 16
## 1984 + + + + + 17
## 2034 + + + + + + 15
## 1972 + + + + + 15
## 4094 + + + + + + + 18
## 1978 + + + + + 15
## 1982 + + + + + 16
## 1970 + + + + + 14
## 4096 + + + + + + + 19
## 2046 + + + + + + 17
## 2036 + + + + + + 16
## 4074 + + + + + + + 16
## 4084 + + + + + + + 17
## 2048 + + + + + + 18
## 4022 + + + + + + 16
## 1974 + + + + + 15
## 2038 + + + + + + 16
## 4086 + + + + + + + 17
## 4024 + + + + + + 17
## 1976 + + + + + 16
## 4066 + + + + + + + 15
## 4076 + + + + + + + 17
## 2040 + + + + + + 17
## 4078 + + + + + + + 17
## 4088 + + + + + + + 18
## 2026 + + + + + + 15
## 3896 + + + + + 15
## 2018 + + + + + + 14
## 3960 + + + + + + 16
## 2030 + + + + + + 16
## 3904 + + + + + 16
## 4070 + + + + + + + 16
## 4068 + + + + + + + 16
## 3892 + + + + + 14
## 4080 + + + + + + + 18
## 2028 + + + + + + 16
## 3968 + + + + + + 17
## 2022 + + + + + + 15
## 3900 + + + + + 15
## 2020 + + + + + + 15
## 3958 + + + + + + 15
## 3956 + + + + + + 15
## 2032 + + + + + + 17
## 1844 + + + + 13
## 3964 + + + + + + 16
## 4072 + + + + + + + 17
## 1908 + + + + + 14
## 3942 + + + + + + 14
## 3954 + + + + + + 14
## 3952 + + + + + + 16
## 2024 + + + + + + 16
## 3950 + + + + + + 15
## 4010 + + + + + + 15
## 3966 + + + + + + 16
## 956 + + + + 15
## 3944 + + + + + + 15
## 3938 + + + + + + 13
## 1020 + + + + + 16
## 3890 + + + + + 13
## 1912 + + + + + 15
## 1848 + + + + 14
## 3946 + + + + + + 14
## 3894 + + + + + 14
## 3962 + + + + + + 15
## 3948 + + + + + + 15
## 1852 + + + + 14
## 4012 + + + + + + 16
## 1018 + + + + + 15
## 4002 + + + + + + 14
## 1916 + + + + + 15
## 4014 + + + + + + 16
## 1906 + + + + + 13
## 3940 + + + + + + 14
## 1890 + + + + + 12
## 960 + + + + 16
## 1024 + + + + + 17
## 3898 + + + + + 14
## 1892 + + + + + 13
## 3004 + + + + + 16
## 3902 + + + + + 15
## 1920 + + + + + 16
## 1856 + + + + 15
## 3068 + + + + + + 17
## 4006 + + + + + + 15
## 4016 + + + + + + 17
## 4004 + + + + + + 15
## 1022 + + + + + 16
## 1910 + + + + + 14
## 3066 + + + + + + 16
## 1894 + + + + + 13
## 1900 + + + + + 14
## 1914 + + + + + 14
## 1898 + + + + + 13
## 1896 + + + + + 14
## 954 + + + + 14
## 3008 + + + + + 17
## 3072 + + + + + + 18
## 1966 + + + + + 15
## 1958 + + + + + 14
## 4008 + + + + + + 16
## 1842 + + + + 12
## 1904 + + + + + 15
## 1918 + + + + + 15
## 3070 + + + + + + 17
## 1902 + + + + + 14
## 1724 + + + + 15
## 3884 + + + + + 14
## 958 + + + + 15
## 1968 + + + + + 16
## 3002 + + + + + 15
## 1728 + + + + 16
## 3888 + + + + + 15
## 1002 + + + + + 14
## 1960 + + + + + 15
## 1850 + + + + 13
## 1954 + + + + + 13
## 3772 + + + + + 16
## 1010 + + + + + 14
## 1846 + + + + 13
## 1788 + + + + + 16
## 1962 + + + + + 14
## 3876 + + + + + 13
## 1964 + + + + + 15
## 3882 + + + + + 13
## 1956 + + + + + 14
## 1014 + + + + + 15
## 3874 + + + + + 12
## 3006 + + + + + 16
## 3880 + + + + + 14
## 1016 + + + + + 16
## 3058 + + + + + + 15
## 1716 + + + + 14
## 1004 + + + + + 15
## 1792 + + + + + 17
## 1012 + + + + + 15
## 3776 + + + + + 17
## 1006 + + + + + 15
## 948 + + + + 14
## 3050 + + + + + + 15
## 1854 + + + + 14
## 3886 + + + + + 14
## 952 + + + + 15
## 3878 + + + + + 13
## 3836 + + + + + + 17
## 1772 + + + + + 15
## 1712 + + + + 15
## 946 + + + + 13
## 3060 + + + + + + 16
## 1710 + + + + 14
## 3756 + + + + + 15
## 1726 + + + + 15
## 1776 + + + + + 16
## 1720 + + + + 15
## 2996 + + + + + 15
## 3062 + + + + + + 16
## 1774 + + + + + 15
## 3820 + + + + + + 16
## 1008 + + + + + 16
## 3764 + + + + + 15
## 3760 + + + + + 16
## 1708 + + + + 14
## 3064 + + + + + + 17
## 1780 + + + + + 15
## 3052 + + + + + + 16
## 3840 + + + + + + 18
## 3054 + + + + + + 16
## 1702 + + + + 13
## 1828 + + + + 12
## 2994 + + + + + 14
## 950 + + + + 14
## 1718 + + + + 14
## 3000 + + + + + 16
## 3758 + + + + + 15
## 1764 + + + + + 14
## 1704 + + + + 14
## 3824 + + + + + + 17
## 1790 + + + + + 16
## 3774 + + + + + 16
## 1766 + + + + + 14
## 1784 + + + + + 16
## 3768 + + + + + 16
## 1700 + + + + 13
## 1836 + + + + 13
## 1768 + + + + + 15
## 3748 + + + + + 14
## 3822 + + + + + + 16
## 3056 + + + + + + 17
## 1770 + + + + + 14
## 3828 + + + + + + 16
## 3750 + + + + + 14
## 994 + + + + + 13
## 1762 + + + + + 13
## 1722 + + + + 14
## 1832 + + + + 13
## 3812 + + + + + + 15
## 2998 + + + + + 15
## 1714 + + + + 13
## 3752 + + + + + 15
## 1782 + + + + + 15
## 3766 + + + + + 15
## 1826 + + + + 11
## 3754 + + + + + 14
## 998 + + + + + 14
## 3818 + + + + + + 15
## 3838 + + + + + + 17
## 3814 + + + + + + 15
## 1840 + + + + 14
## 1698 + + + + 12
## 3770 + + + + + 15
## 3832 + + + + + + 17
## 1706 + + + + 13
## 1786 + + + + + 15
## 3746 + + + + + 13
## 3816 + + + + + + 16
## 3042 + + + + + + 14
## 1778 + + + + + 14
## 3810 + + + + + + 14
## 3762 + + + + + 14
## 888 + + + + 14
## 996 + + + + + 14
## 1830 + + + + 12
## 700 + + + 14
## 1834 + + + + 12
## 3830 + + + + + + 16
## 1260 + + + + 14
## 3834 + + + + + + 16
## 1000 + + + + + 15
## 3046 + + + + + + 15
## 2936 + + + + + 15
## 1200 + + + 14
## 2748 + + + + 15
## 1198 + + + 13
## 3826 + + + + + + 15
## 3044 + + + + + + 15
## 896 + + + + 15
## 1196 + + + 13
## 1264 + + + + 15
## 1190 + + + 12
## 1252 + + + + 13
## 1838 + + + + 13
## 1516 + + + + + 15
## 1262 + + + + 14
## 1188 + + + 12
## 2944 + + + + + 16
## 3244 + + + + 14
## 1192 + + + 13
## 704 + + + 15
## 1506 + + + + + 13
## 764 + + + + 15
## 3308 + + + + + 15
## 1212 + + + 14
## 1508 + + + + + 14
## 1254 + + + + 13
## 1514 + + + + + 14
## 1518 + + + + + 15
## 1276 + + + + 15
## 3048 + + + + + + 16
## 1216 + + + 15
## 1510 + + + + + 14
## 1256 + + + + 14
## 3248 + + + + 15
## 1250 + + + + 12
## 1454 + + + + 14
## 1572 + + + 11
## 1520 + + + + + 16
## 824 + + + 13
## 1456 + + + + 15
## 1446 + + + + 13
## 1258 + + + + 13
## 2812 + + + + + 16
## 2752 + + + + 16
## 3246 + + + + 14
## 1204 + + + 13
## 1214 + + + 14
## 3949 + + + + + + 12
## 1522 + + + + + 14
## 1278 + + + + 15
## 3236 + + + + 13
## 872 + + + + 13
## 1452 + + + + 14
## 3620 + + + + 12
## 1280 + + + + 16
## 3312 + + + + + 16
## 3951 + + + + + + 13
## 1588 + + + 12
## 3564 + + + + + + 16
## 3238 + + + + 13
## 1206 + + + 13
## 3300 + + + + + 14
## 1268 + + + + 14
## 1530 + + + + + 15
## 886 + + + + 13
## 1186 + + + 11
## 1534 + + + + + 16
## 1532 + + + + + 16
## 1444 + + + + 13
## 3260 + + + + 15
## 1270 + + + + 14
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## logLik AICc delta weight
## 4028 -292.796 626.6 0.00 0.166
## 4026 -294.767 627.7 1.09 0.096
## 4090 -293.488 628.0 1.38 0.083
## 1980 -294.968 628.1 1.49 0.079
## 4092 -292.379 628.7 2.08 0.059
## 4032 -292.748 629.4 2.82 0.041
## 2044 -294.288 629.6 2.98 0.037
## 2042 -295.750 629.7 3.06 0.036
## 4018 -297.159 629.7 3.08 0.036
## 4082 -296.048 630.3 3.65 0.027
## 4030 -294.657 630.3 3.72 0.026
## 4020 -296.155 630.5 3.86 0.024
## 1984 -294.740 630.5 3.89 0.024
## 2034 -297.580 630.6 3.93 0.023
## 1972 -297.651 630.7 4.07 0.022
## 4094 -293.487 630.9 4.30 0.019
## 1978 -297.780 631.0 4.33 0.019
## 1982 -296.517 631.2 4.59 0.017
## 1970 -299.313 631.3 4.66 0.016
## 4096 -292.280 631.5 4.87 0.015
## 2046 -295.245 631.5 4.90 0.014
## 2036 -296.897 632.0 5.35 0.011
## 4074 -296.901 632.0 5.36 0.011
## 4084 -295.625 632.3 5.66 0.010
## 2048 -294.177 632.3 5.68 0.010
## 4022 -297.134 632.5 5.82 0.009
## 1974 -298.558 632.5 5.88 0.009
## 2038 -297.362 632.9 6.28 0.007
## 4086 -296.031 633.1 6.47 0.007
## 4024 -296.088 633.2 6.58 0.006
## 1976 -297.538 633.3 6.63 0.006
## 4066 -299.482 634.4 7.73 0.003
## 4076 -296.803 634.6 8.01 0.003
## 2040 -296.863 634.8 8.13 0.003
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## 4088 -295.492 634.9 8.31 0.003
## 2026 -299.861 635.1 8.49 0.002
## 3896 -300.149 635.7 9.06 0.002
## 2018 -301.600 635.9 9.24 0.002
## 3960 -299.213 636.6 9.98 0.001
## 2030 -299.264 636.7 10.08 0.001
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## 4068 -299.479 637.1 10.51 0.001
## 3892 -302.380 637.4 10.80 0.001
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## 2022 -301.315 638.0 11.40 0.001
## 3900 -301.429 638.3 11.62 0.000
## 2020 -301.590 638.6 11.95 0.000
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## 3956 -301.813 639.0 12.39 0.000
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## 3938 -305.734 641.5 14.84 0.000
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## 3890 -305.828 641.7 15.03 0.000
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## 4012 -302.027 642.2 15.61 0.000
## 1018 -303.443 642.3 15.65 0.000
## 4002 -304.924 642.5 15.89 0.000
## 1916 -303.597 642.6 15.96 0.000
## 4014 -302.250 642.7 16.05 0.000
## 1906 -306.381 642.8 16.13 0.000
## 3940 -305.168 643.0 16.37 0.000
## 1890 -307.912 643.2 16.59 0.000
## 960 -302.572 643.3 16.70 0.000
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## 3898 -305.529 643.7 17.10 0.000
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## 1920 -303.073 644.3 17.70 0.000
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## 4006 -304.642 644.7 18.05 0.000
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## 1022 -303.344 644.9 18.24 0.000
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## 1894 -307.635 645.3 18.64 0.000
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## 1898 -307.739 645.5 18.85 0.000
## 1896 -306.481 645.6 19.00 0.000
## 954 -306.587 645.8 19.21 0.000
## 3008 -302.493 646.0 19.39 0.000
## 3072 -301.095 646.1 19.52 0.000
## 1966 -305.433 646.3 19.63 0.000
## 1958 -307.251 647.2 20.54 0.000
## 4008 -304.539 647.3 20.63 0.000
## 1842 -310.028 647.4 20.82 0.000
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## 3884 -307.762 648.2 21.56 0.000
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## 2574 -375.150 767.8 141.17 0.000
## 2638 -374.087 768.1 141.44 0.000
## 2078 -375.426 768.4 141.72 0.000
## 2589 -377.861 768.6 141.95 0.000
## 2590 -375.011 769.9 143.29 0.000
## Models ranked by AICc(x)top <- weightable(res_stimuli_modality)
top <- top[top$aicc <= min(top$aicc) + 2,]
top## model
## 1 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## 2 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + character_identification + n_repetitions_sentence + n_repetitions_video
## 3 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video
## 4 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + character_identification + n_repetitions_sentence + n_repetitions_video
## 5 d_calc ~ 1 + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video
## 6 d_calc ~ 1 + sentence_structure + agent_argument_type_clean + patient_argument_type_clean + stimuli_actor + stimuli_modality + presentation_type + test_mass_or_distributed + practice_phase + n_repetitions_sentence + n_repetitions_video
## aicc weights
## 1 628.1178 0.11822538
## 2 628.1178 0.11822538
## 3 629.6108 0.05604127
## 4 629.6108 0.05604127
## 5 629.6825 0.05406772
## 6 629.6825 0.05406772summary(res_stimuli_modality@objects[[1]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -294.9680 614.1518 621.9360 664.3994 628.1178
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 89) = 614.1518, p-val < .0001
##
## Test of Moderators (coefficients 2:16):
## QM(df = 15) = 169.7196, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.2346 0.2338 -1.0033 0.3157
## agent_argument_type_cleannoun_phrase -0.0189 0.1512 -0.1251 0.9005
## agent_argument_type_cleanpronoun -1.0490 0.1746 -6.0090 <.0001
## agent_argument_type_cleanvarying_agent 0.3263 0.1596 2.0446 0.0409
## patient_argument_type_cleannoun -0.1362 0.1025 -1.3284 0.1841
## patient_argument_type_cleannoun_phrase 1.0182 0.1517 6.7107 <.0001
## patient_argument_type_cleanpronoun 1.0479 0.1475 7.1042 <.0001
## patient_argument_type_cleanvarying_patient -0.6836 0.1723 -3.9679 <.0001
## stimuli_actorperson -0.5913 0.1249 -4.7352 <.0001
## stimuli_modalityvideo 0.9659 0.1515 6.3765 <.0001
## presentation_typeimmediate_after 0.7902 0.1866 4.2361 <.0001
## presentation_typesimultaneous 0.5727 0.1857 3.0842 0.0020
## test_mass_or_distributedmass 0.4082 0.1024 3.9845 <.0001
## character_identificationyes 0.2318 0.0977 2.3717 0.0177
## n_repetitions_sentence 0.0220 0.0095 2.3166 0.0205
## n_repetitions_video -0.1757 0.0349 -5.0278 <.0001
## ci.lb ci.ub
## intrcpt -0.6928 0.2236
## agent_argument_type_cleannoun_phrase -0.3153 0.2774
## agent_argument_type_cleanpronoun -1.3912 -0.7069 ***
## agent_argument_type_cleanvarying_agent 0.0135 0.6391 *
## patient_argument_type_cleannoun -0.3371 0.0647
## patient_argument_type_cleannoun_phrase 0.7208 1.3156 ***
## patient_argument_type_cleanpronoun 0.7588 1.3371 ***
## patient_argument_type_cleanvarying_patient -1.0212 -0.3459 ***
## stimuli_actorperson -0.8360 -0.3465 ***
## stimuli_modalityvideo 0.6690 1.2628 ***
## presentation_typeimmediate_after 0.4246 1.1559 ***
## presentation_typesimultaneous 0.2088 0.9367 **
## test_mass_or_distributedmass 0.2074 0.6090 ***
## character_identificationyes 0.0402 0.4234 *
## n_repetitions_sentence 0.0034 0.0405 *
## n_repetitions_video -0.2442 -0.1072 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_stimuli_modality, type="s")
summary(res_stimuli_modality@objects[[2]])##
## Multivariate Meta-Analysis Model (k = 105; method: ML)
##
## logLik Deviance AIC BIC AICc
## -294.9680 614.1518 621.9360 664.3994 628.1178
##
## Variance Components: none
##
## Test for Residual Heterogeneity:
## QE(df = 89) = 614.1518, p-val < .0001
##
## Test of Moderators (coefficients 2:16):
## QM(df = 15) = 169.7196, p-val < .0001
##
## Model Results:
##
## estimate se zval pval
## intrcpt -0.2346 0.2338 -1.0033 0.3157
## sentence_structuretransitive -0.6836 0.1723 -3.9679 <.0001
## agent_argument_type_cleannoun_phrase -0.0189 0.1512 -0.1251 0.9005
## agent_argument_type_cleanpronoun -1.0490 0.1746 -6.0090 <.0001
## agent_argument_type_cleanvarying_agent 0.3263 0.1596 2.0446 0.0409
## patient_argument_type_cleannoun 0.5474 0.1640 3.3379 0.0008
## patient_argument_type_cleannoun_phrase 1.7018 0.2279 7.4665 <.0001
## patient_argument_type_cleanpronoun 1.7315 0.2302 7.5219 <.0001
## stimuli_actorperson -0.5913 0.1249 -4.7352 <.0001
## stimuli_modalityvideo 0.9659 0.1515 6.3765 <.0001
## presentation_typeimmediate_after 0.7902 0.1866 4.2361 <.0001
## presentation_typesimultaneous 0.5727 0.1857 3.0842 0.0020
## test_mass_or_distributedmass 0.4082 0.1024 3.9845 <.0001
## character_identificationyes 0.2318 0.0977 2.3717 0.0177
## n_repetitions_sentence 0.0220 0.0095 2.3166 0.0205
## n_repetitions_video -0.1757 0.0349 -5.0278 <.0001
## ci.lb ci.ub
## intrcpt -0.6928 0.2236
## sentence_structuretransitive -1.0212 -0.3459 ***
## agent_argument_type_cleannoun_phrase -0.3153 0.2774
## agent_argument_type_cleanpronoun -1.3912 -0.7069 ***
## agent_argument_type_cleanvarying_agent 0.0135 0.6391 *
## patient_argument_type_cleannoun 0.2260 0.8689 ***
## patient_argument_type_cleannoun_phrase 1.2551 2.1485 ***
## patient_argument_type_cleanpronoun 1.2803 2.1827 ***
## stimuli_actorperson -0.8360 -0.3465 ***
## stimuli_modalityvideo 0.6690 1.2628 ***
## presentation_typeimmediate_after 0.4246 1.1559 ***
## presentation_typesimultaneous 0.2088 0.9367 **
## test_mass_or_distributedmass 0.2074 0.6090 ***
## character_identificationyes 0.0402 0.4234 *
## n_repetitions_sentence 0.0034 0.0405 *
## n_repetitions_video -0.2442 -0.1072 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(res_stimuli_modality, type="s")
eval(metafor:::.glmulti)
coef(res_stimuli_modality)## Estimate Uncond. variance
## mean_age 0.0000427903 8.242971e-09
## practice_phaseyes 0.0710394305 1.069194e-02
## sentence_structuretransitive -0.3141608853 1.127777e-01
## patient_argument_type_cleanvarying_patient -0.3141608853 1.127777e-01
## character_identificationyes 0.1134302294 1.586680e-02
## n_repetitions_sentence 0.0144506224 1.490095e-04
## intrcpt -0.1984816941 8.726582e-02
## agent_argument_type_cleannoun_phrase 0.0055412423 2.329052e-02
## agent_argument_type_cleanpronoun -1.0413154409 3.238753e-02
## agent_argument_type_cleanvarying_agent 0.3026394206 2.732623e-02
## patient_argument_type_cleannoun 0.1864858684 1.170563e-01
## patient_argument_type_cleannoun_phrase 1.3309291031 1.359046e-01
## patient_argument_type_cleanpronoun 1.3460888937 1.352170e-01
## stimuli_actorperson -0.6325170153 1.726520e-02
## stimuli_modalityvideo 0.9470042263 2.341994e-02
## presentation_typeimmediate_after 0.7263806611 4.262262e-02
## presentation_typesimultaneous 0.4616392679 4.485019e-02
## test_mass_or_distributedmass 0.4360120459 1.188102e-02
## n_repetitions_video -0.1502661101 1.935324e-03
## Nb models Importance
## mean_age 16 0.2682378
## practice_phaseyes 16 0.4267868
## sentence_structuretransitive 16 0.5000000
## patient_argument_type_cleanvarying_patient 16 0.5000000
## character_identificationyes 16 0.5751023
## n_repetitions_sentence 16 0.7076217
## intrcpt 32 1.0000000
## agent_argument_type_cleannoun_phrase 32 1.0000000
## agent_argument_type_cleanpronoun 32 1.0000000
## agent_argument_type_cleanvarying_agent 32 1.0000000
## patient_argument_type_cleannoun 32 1.0000000
## patient_argument_type_cleannoun_phrase 32 1.0000000
## patient_argument_type_cleanpronoun 32 1.0000000
## stimuli_actorperson 32 1.0000000
## stimuli_modalityvideo 32 1.0000000
## presentation_typeimmediate_after 32 1.0000000
## presentation_typesimultaneous 32 1.0000000
## test_mass_or_distributedmass 32 1.0000000
## n_repetitions_video 32 1.0000000
## +/- (alpha=0.05)
## mean_age 0.0001779467
## practice_phaseyes 0.2026638430
## sentence_structuretransitive 0.6582029183
## patient_argument_type_cleanvarying_patient 0.6582029183
## character_identificationyes 0.2468839124
## n_repetitions_sentence 0.0239251759
## intrcpt 0.5789888110
## agent_argument_type_cleannoun_phrase 0.2991146441
## agent_argument_type_cleanpronoun 0.3527255930
## agent_argument_type_cleanvarying_agent 0.3239947489
## patient_argument_type_cleannoun 0.6705720850
## patient_argument_type_cleannoun_phrase 0.7225454772
## patient_argument_type_cleanpronoun 0.7207152498
## stimuli_actorperson 0.2575336209
## stimuli_modalityvideo 0.2999445450
## presentation_typeimmediate_after 0.4046393964
## presentation_typesimultaneous 0.4150784923
## test_mass_or_distributedmass 0.2136362809
## n_repetitions_video 0.0862233568mmi <- as.data.frame(coef(res_stimuli_modality))
mmi <- data.frame(Estimate=mmi$Est, SE=sqrt(mmi$Uncond), Importance=mmi$Importance, row.names=row.names(mmi))
mmi$z <- mmi$Estimate / mmi$SE
mmi$p <- 2*pnorm(abs(mmi$z), lower.tail=FALSE)
names(mmi) <- c("Estimate", "Std. Error", "Importance", "z value", "Pr(>|z|)")
mmi$ci.lb <- mmi[[1]] - qnorm(.975) * mmi[[2]]
mmi$ci.ub <- mmi[[1]] + qnorm(.975) * mmi[[2]]
mmi <- mmi[order(mmi$Importance, decreasing=TRUE), c(1,2,4:7,3)]
round(mmi, 4)## Estimate Std. Error z value Pr(>|z|)
## intrcpt -0.1985 0.2954 -0.6719 0.5017
## agent_argument_type_cleannoun_phrase 0.0055 0.1526 0.0363 0.9710
## agent_argument_type_cleanpronoun -1.0413 0.1800 -5.7862 0.0000
## agent_argument_type_cleanvarying_agent 0.3026 0.1653 1.8308 0.0671
## patient_argument_type_cleannoun 0.1865 0.3421 0.5451 0.5857
## patient_argument_type_cleannoun_phrase 1.3309 0.3687 3.6103 0.0003
## patient_argument_type_cleanpronoun 1.3461 0.3677 3.6606 0.0003
## stimuli_actorperson -0.6325 0.1314 -4.8138 0.0000
## stimuli_modalityvideo 0.9470 0.1530 6.1881 0.0000
## presentation_typeimmediate_after 0.7264 0.2065 3.5184 0.0004
## presentation_typesimultaneous 0.4616 0.2118 2.1798 0.0293
## test_mass_or_distributedmass 0.4360 0.1090 4.0001 0.0001
## n_repetitions_video -0.1503 0.0440 -3.4157 0.0006
## n_repetitions_sentence 0.0145 0.0122 1.1838 0.2365
## character_identificationyes 0.1134 0.1260 0.9005 0.3679
## patient_argument_type_cleanvarying_patient -0.3142 0.3358 -0.9355 0.3495
## sentence_structuretransitive -0.3142 0.3358 -0.9355 0.3495
## practice_phaseyes 0.0710 0.1034 0.6870 0.4921
## mean_age 0.0000 0.0001 0.4713 0.6374
## ci.lb ci.ub Importance
## intrcpt -0.7775 0.3805 1.0000
## agent_argument_type_cleannoun_phrase -0.2936 0.3047 1.0000
## agent_argument_type_cleanpronoun -1.3940 -0.6886 1.0000
## agent_argument_type_cleanvarying_agent -0.0214 0.6266 1.0000
## patient_argument_type_cleannoun -0.4841 0.8571 1.0000
## patient_argument_type_cleannoun_phrase 0.6084 2.0535 1.0000
## patient_argument_type_cleanpronoun 0.6254 2.0668 1.0000
## stimuli_actorperson -0.8901 -0.3750 1.0000
## stimuli_modalityvideo 0.6471 1.2469 1.0000
## presentation_typeimmediate_after 0.3217 1.1310 1.0000
## presentation_typesimultaneous 0.0466 0.8767 1.0000
## test_mass_or_distributedmass 0.2224 0.6496 1.0000
## n_repetitions_video -0.2365 -0.0640 1.0000
## n_repetitions_sentence -0.0095 0.0384 0.7076
## character_identificationyes -0.1335 0.3603 0.5751
## patient_argument_type_cleanvarying_patient -0.9724 0.3440 0.5000
## sentence_structuretransitive -0.9724 0.3440 0.5000
## practice_phaseyes -0.1316 0.2737 0.4268
## mean_age -0.0001 0.0002 0.2682